34 citations · 41 across the 15 of their papers we have counts for
17 papers
Learning as Deepfakes Evolve: RF-Prompt for Continual Audio Deepfake Detection
Yuankun Xie, Xiaoxuan Guo, Xiaopeng Wang +3
Continual audio deepfake detection requires learning newly emerging deepfake methods while retaining discrimination of previously encountered speech. Existing dataset-incremental e…
Boundary and Intra-Segment Learning for Partial Audio Deepfake Localization
Zhe Ye, Xiangui Kang, Minhua Huang +3
Partial audio deepfakes manipulate only selected speech regions, making them difficult to be localized. Existing methods exploit boundary cues for partial deepfake localization, bu…
Not All Attacks Are Learned Equally in Speech Deepfake Detection
Avantika Singh, Aurosweta Mahapatra, Ismail Rasim Ulgen +3
Speech deepfake detection (SDD) models are trained on multi-attack datasets containing diverse spoofing systems, such as text-to-speech (TTS) and voice conversion (VC). In standard…
BiMTokenizer: Preserving Semantic-Acoustic Balance in Low-Bitrate Speech Tokenization via Bidirectional State-Space Modeling
Xin Zhang, Lin Li, Chuanbo Liu +2
Speech codecs serve as bridges between continuous speech signals and large language models, yet face an inherent conflict between acoustic fidelity and semantic preservation. To mi…
AffectDF: The Most Comprehensive Benchmark for Speech Deepfake Detection against Emotionally Expressive Attacks
Aurosweta Mahapatra, Xiutian Zhao, Shreeram Suresh Chandra +7
Speech deepfake detection (SDD) systems achieve strong performance on conventional benchmarks; however, existing datasets provide limited coverage of emotionally expressive and rec…
RADAR Challenge 2026: Robust Audio Deepfake Recognition under Media Transformations
Hieu-Thi Luong, Xuechen Liu, Ivan Kukanov +2
RADAR Challenge 2026 is an APSIPA Grand Challenge on Robust Audio Deepfake Recognition under Media Transformations, designed to simulate realistic media conditions in real-world au…
Stream-Voice-Anon: Enhancing Utility of Real-Time Speaker Anonymization via Neural Audio Codec and Language Models
Nikita Kuzmin, Songting Liu, Kong Aik Lee +1
Protecting speaker identity is crucial for online voice applications, yet streaming speaker anonymization (SA) remains underexplored. Recent research has demonstrated that neural a…
U3-xi: Pushing the Boundaries of Speaker Recognition by Incorporating Uncertainty
Junjie Li, Kong Aik Lee
An utterance-level speaker embedding is typically obtained by aggregating a sequence of frame-level representations. However, in real-world scenarios, individual frames encode not…
Speaking Clearly: A Simplified Whisper-Based Codec for Low-Bitrate Speech Coding
Xin Zhang, Lin Li, Xiangni Lu +2
Speech codecs serve as bridges between continuous speech signals and large language models, yet face an inherent conflict between acoustic fidelity and semantic preservation. To mi…
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…
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…
Robust Localization of Partially Fake Speech: Metrics and Out-of-Domain Evaluation
Hieu-Thi Luong, Inbal Rimon, Haim Permuter +2
Partial audio deepfake localization poses unique challenges and remain underexplored compared to full-utterance spoofing detection. While recent methods report strong in-domain per…
NTU-NPU System for Voice Privacy 2024 Challenge
Nikita Kuzmin, Hieu-Thi Luong, Jixun Yao +3
In this work, we describe our submissions for the Voice Privacy Challenge 2024. Rather than proposing a novel speech anonymization system, we enhance the provided baselines to meet…
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…
LlamaPartialSpoof: An LLM-Driven Fake Speech Dataset Simulating Disinformation Generation
Hieu-Thi Luong, Haoyang Li, Lin Zhang +2
Previous fake speech datasets were constructed from a defender's perspective to develop countermeasure (CM) systems without considering diverse motivations of attackers. To better…
NPU-NTU System for Voice Privacy 2024 Challenge
Jixun Yao, Nikita Kuzmin, Qing Wang +6
Speaker anonymization is an effective privacy protection solution that conceals the speaker's identity while preserving the linguistic content and paralinguistic information of the…
Temporal-Channel Modeling in Multi-head Self-Attention for Synthetic Speech Detection
Duc-Tuan Truong, Ruijie Tao, Tuan Nguyen +3
Recent synthetic speech detectors leveraging the Transformer model have superior performance compared to the convolutional neural network counterparts. This improvement could be du…