8 papers
Teffic-Audio: Tell Fact from Fiction
Wan Lin, Li Wang, Jindong Wang +2
The paper presents Teffic-Audio, a speech deepfake detection system that uses a Conformer-based encoder with attentive pooling and a training recipe focused on multi-source data an…
VoxSafeBench: Not Just What Is Said, but Who, How, and Where
Yuxiang Wang, Hongyu Liu, Yijiang Xu +9
As speech language models (SLMs) transition from personal devices into shared, multi-user environments, their responses must account for far more than the words alone. Who is speak…
DFALLM: Achieving Generalizable Multitask Deepfake Detection by Optimizing Audio LLM Components
Yupei Li, Li Wang, Yuxiang Wang +5
Audio deepfake detection has recently garnered public concern due to its implications for security and reliability. Traditional deep learning methods have been widely applied to th…
SpeechJudge: Towards Human-Level Judgment for Speech Naturalness
Xueyao Zhang, Chaoren Wang, Huan Liao +8
Aligning large generative models with human feedback is a critical challenge. In speech synthesis, this is particularly pronounced due to the lack of a large-scale human preference…
Over-the-Air Adversarial Attack Detection: from Datasets to Defenses
Li Wang, Xiaoyan Lei, Haorui He +3
Automatic Speaker Verification (ASV) systems can be used for voice-enabled applications for identity verification. However, recent studies have exposed these systems' vulnerabiliti…
Audio Deepfake Verification
Li Wang, Junyi Ao, Linyong Gan +3
With the rapid development of deepfake technology, simply making a binary judgment of true or false on audio is no longer sufficient to meet practical needs. Accurately determining…