4 citations · 5 across the 7 of their papers we have counts for
9 papers · 1 filter
P2Mark: Plug-and-play Parameter-level Watermarking for Neural Speech Generation
Yong Ren, Jiangyan Yi, Tao Wang +7
Neural speech generation (NSG) has rapidly advanced as a key component of artificial intelligence-generated content, enabling the generation of high-quality, highly realistic speec…
Region-Based Optimization in Continual Learning for Audio Deepfake Detection
Yujie Chen, Jiangyan Yi, Cunhang Fan +10
Rapid advancements in speech synthesis and voice conversion bring convenience but also new security risks, creating an urgent need for effective audio deepfake detection. Although…
Utilizing Speaker Profiles for Impersonation Audio Detection
Hao Gu, JiangYan Yi, Chenglong Wang +5
Fake audio detection is an emerging active topic. A growing number of literatures have aimed to detect fake utterance, which are mostly generated by Text-to-speech (TTS) or voice c…
An Unsupervised Domain Adaptation Method for Locating Manipulated Region in partially fake Audio
Siding Zeng, Jiangyan Yi, Jianhua Tao +4
When the task of locating manipulation regions in partially-fake audio (PFA) involves cross-domain datasets, the performance of deep learning models drops significantly due to the…
RawBMamba: End-to-End Bidirectional State Space Model for Audio Deepfake Detection
Yujie Chen, Jiangyan Yi, Jun Xue +7
Fake artefacts for discriminating between bonafide and fake audio can exist in both short- and long-range segments. Therefore, combining local and global feature information can ef…
Towards Robust Audio Deepfake Detection: A Evolving Benchmark for Continual Learning
Xiaohui Zhang, Jiangyan Yi, Jianhua Tao
The rise of advanced large language models such as GPT-4, GPT-4o, and the Claude family has made fake audio detection increasingly challenging. Traditional fine-tuning methods stru…