116 citations · 125 across the 13 of their papers we have counts for
13 papers
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…
What to Remember: Self-Adaptive Continual Learning for Audio Deepfake Detection
Xiaohui Zhang, Jiangyan Yi, Chenglong Wang +3
The rapid evolution of speech synthesis and voice conversion has raised substantial concerns due to the potential misuse of such technology, prompting a pressing need for effective…
Do You Remember? Overcoming Catastrophic Forgetting for Fake Audio Detection
Xiaohui Zhang, Jiangyan Yi, Jianhua Tao +2
Current fake audio detection algorithms have achieved promising performances on most datasets. However, their performance may be significantly degraded when dealing with audio of a…
TST: Time-Sparse Transducer for Automatic Speech Recognition
Xiaohui Zhang, Mangui Liang, Zhengkun Tian +2
End-to-end model, especially Recurrent Neural Network Transducer (RNN-T), has achieved great success in speech recognition. However, transducer requires a great memory footprint an…
Adaptive Fake Audio Detection with Low-Rank Model Squeezing
Xiaohui Zhang, Jiangyan Yi, Jianhua Tao +3
The rapid advancement of spoofing algorithms necessitates the development of robust detection methods capable of accurately identifying emerging fake audio. Traditional approaches,…
Scaling Speech Technology to 1,000+ Languages
Vineel Pratap, Andros Tjandra, Bowen Shi +13
Expanding the language coverage of speech technology has the potential to improve access to information for many more people. However, current speech technology is restricted to ab…
TorchAudio-Squim: Reference-less Speech Quality and Intelligibility measures in TorchAudio
Anurag Kumar, Ke Tan, Zhaoheng Ni +4
Measuring quality and intelligibility of a speech signal is usually a critical step in development of speech processing systems. To enable this, a variety of metrics to measure qua…
ESPnet-ST-v2: Multipurpose Spoken Language Translation Toolkit
Brian Yan, Jiatong Shi, Yun Tang +13
ESPnet-ST-v2 is a revamp of the open-source ESPnet-ST toolkit necessitated by the broadening interests of the spoken language translation community. ESPnet-ST-v2 supports 1) offlin…