4 papers
Does Current Deepfake Audio Detection Model Effectively Detect ALM-based Deepfake Audio?
Yuankun Xie, Chenxu Xiong, Xiaopeng Wang +9
Currently, Audio Language Models (ALMs) are rapidly advancing due to the developments in large language models and audio neural codecs. These ALMs have significantly lowered the ba…
Temporal Variability and Multi-Viewed Self-Supervised Representations to Tackle the ASVspoof5 Deepfake Challenge
Yuankun Xie, Xiaopeng Wang, Zhiyong Wang +4
ASVspoof5, the fifth edition of the ASVspoof series, is one of the largest global audio security challenges. It aims to advance the development of countermeasure (CM) to discrimina…
FSD: An Initial Chinese Dataset for Fake Song Detection
Yuankun Xie, Jingjing Zhou, Xiaolin Lu +4
Singing voice synthesis and singing voice conversion have significantly advanced, revolutionizing musical experiences. However, the rise of "Deepfake Songs" generated by these tech…
An Efficient Temporary Deepfake Location Approach Based Embeddings for Partially Spoofed Audio Detection
Yuankun Xie, Haonan Cheng, Yutian Wang +1
Partially spoofed audio detection is a challenging task, lying in the need to accurately locate the authenticity of audio at the frame level. To address this issue, we propose a fi…