25 citations · 41 across the 14 of their papers we have counts for
14 papers
TACO: Tool-Augmented Credit Optimization for Agentic Tool Use
Mingkuan Feng, Jinyang Wu, Hao Gu +5
Agentic multimodal models perform diverse operations on an image via code and reason over the returned view, an effective paradigm for fine-grained visual question answering. Howev…
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…
WMCodec: End-to-End Neural Speech Codec with Deep Watermarking for Authenticity Verification
Junzuo Zhou, Jiangyan Yi, Yong Ren +3
Recent advances in speech spoofing necessitate stronger verification mechanisms in neural speech codecs to ensure authenticity. Current methods embed numerical watermarks before co…
Pandora's Box or Aladdin's Lamp: A Comprehensive Analysis Revealing the Role of RAG Noise in Large Language Models
Jinyang Wu, Shuai Zhang, Feihu Che +4
Retrieval-Augmented Generation (RAG) has emerged as a crucial method for addressing hallucinations in large language models (LLMs). While recent research has extended RAG models to…
ADD 2023: Towards Audio Deepfake Detection and Analysis in the Wild
Jiangyan Yi, Chu Yuan Zhang, Jianhua Tao +5
The growing prominence of the field of audio deepfake detection is driven by its wide range of applications, notably in protecting the public from potential fraud and other malicio…
TraceableSpeech: Towards Proactively Traceable Text-to-Speech with Watermarking
Junzuo Zhou, Jiangyan Yi, Tao Wang +5
Various threats posed by the progress in text-to-speech (TTS) have prompted the need to reliably trace synthesized speech. However, contemporary approaches to this task involve add…
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…
Fewer-token Neural Speech Codec with Time-invariant Codes
Yong Ren, Tao Wang, Jiangyan Yi +4
Language model based text-to-speech (TTS) models, like VALL-E, have gained attention for their outstanding in-context learning capability in zero-shot scenarios. Neural speech code…
Distinguishing Neural Speech Synthesis Models Through Fingerprints in Speech Waveforms
Chu Yuan Zhang, Jiangyan Yi, Jianhua Tao +2
Recent strides in neural speech synthesis technologies, while enjoying widespread applications, have nonetheless introduced a series of challenges, spurring interest in the defence…
Audio Deepfake Detection: A Survey
Jiangyan Yi, Chenglong Wang, Jianhua Tao +3
Audio deepfake detection is an emerging active topic. A growing number of literatures have aimed to study deepfake detection algorithms and achieved effective performance, the prob…
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…
TO-Rawnet: Improving RawNet with TCN and Orthogonal Regularization for Fake Audio Detection
Chenglong Wang, Jiangyan Yi, Jianhua Tao +4
Current fake audio detection relies on hand-crafted features, which lose information during extraction. To overcome this, recent studies use direct feature extraction from raw audi…
Detection of Cross-Dataset Fake Audio Based on Prosodic and Pronunciation Features
Chenglong Wang, Jiangyan Yi, Jianhua Tao +3
Existing fake audio detection systems perform well in in-domain testing, but still face many challenges in out-of-domain testing. This is due to the mismatch between the training a…
EmoFake: An Initial Dataset for Emotion Fake Audio Detection
Yan Zhao, Jiangyan Yi, Jianhua Tao +3
Many datasets have been designed to further the development of fake audio detection, such as datasets of the ASVspoof and ADD challenges. However, these datasets do not consider a…