7 papers
AT-ADD: All-Type Audio Deepfake Detection Challenge Evaluation Plan
Yuankun Xie, Haonan Cheng, Jiayi Zhou +10
The rapid advancement of Audio Large Language Models (ALLMs) has enabled cost-effective, high-fidelity generation and manipulation of both speech and non-speech audio, including so…
Detect All-Type Deepfake Audio: Wavelet Prompt Tuning for Enhanced Auditory Perception
Yuankun Xie, Ruibo Fu, Zhiyong Wang +5
The rapid advancement of audio generation technologies has escalated the risks of malicious deepfake audio across speech, sound, singing voice, and music, threatening multimedia se…
Interpretable All-Type Audio Deepfake Detection with Audio LLMs via Frequency-Time Reinforcement Learning
Yuankun Xie, Xiaoxuan Guo, Jiayi Zhou +6
Recent advances in audio large language models (ALLMs) have made high-quality synthetic audio widely accessible, increasing the risk of malicious audio deepfakes across speech, env…
Fake Speech Wild: Detecting Deepfake Speech on Social Media Platform
Yuankun Xie, Ruibo Fu, Xiaopeng Wang +5
The rapid advancement of speech generation technology has led to the widespread proliferation of deepfake speech across social media platforms. While deepfake audio countermeasures…
RPRA-ADD: Forgery Trace Enhancement-Driven Audio Deepfake Detection
Ruibo Fu, Xiaopeng Wang, Zhengqi Wen +8
Existing methods for deepfake audio detection have demonstrated some effectiveness. However, they still face challenges in generalizing to new forgery techniques and evolving attac…
Neural Codec Source Tracing: Toward Comprehensive Attribution in Open-Set Condition
Yuankun Xie, Xiaopeng Wang, Zhiyong Wang +7
Current research in audio deepfake detection is gradually transitioning from binary classification to multi-class tasks, referred as audio deepfake source tracing task. However, ex…