activity
20232026
most citedSpatial Reconstructed Local Attention Res2Net with F0 Subband for Fake Speech Detection

17 citations · 36 across the 8 of their papers we have counts for

collaborators

8 papers

eess.AS2026

Beyond Speech: Dual-Domain SSL Fusion for Unified All-Type Audio Deepfake Detection

Cunhang Fan, Junqin Cao, Tian Gao +4

Unified all-type audio deepfake detection aims to determine whether an input clip is real or fake when its audio type may be speech, environmental sound, singing voice, or music. E…

cs.SD2024

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…

cs.SD2024

Frequency-mix Knowledge Distillation for Fake Speech Detection

Cunhang Fan, Shunbo Dong, Jun Xue +3

In the telephony scenarios, the fake speech detection (FSD) task to combat speech spoofing attacks is challenging. Data augmentation (DA) methods are considered effective means to…

cs.CL2024★ 8 cited

Progressive Distillation Based on Masked Generation Feature Method for Knowledge Graph Completion

Cunhang Fan, Yujie Chen, Jun Xue +3

In recent years, knowledge graph completion (KGC) models based on pre-trained language model (PLM) have shown promising results. However, the large number of parameters and high co…

cs.SD2023★ 10 cited

Dual-Branch Knowledge Distillation for Noise-Robust Synthetic Speech Detection

Cunhang Fan, Mingming Ding, Jianhua Tao +4

Most research in synthetic speech detection (SSD) focuses on improving performance on standard noise-free datasets. However, in actual situations, noise interference is usually pre…

eess.SP2023

DGSD: Dynamical Graph Self-Distillation for EEG-Based Auditory Spatial Attention Detection

Cunhang Fan, Hongyu Zhang, Wei Huang +5

Auditory Attention Detection (AAD) aims to detect target speaker from brain signals in a multi-speaker environment. Although EEG-based AAD methods have shown promising results in r…

cs.SD2023★ 17 cited

Spatial Reconstructed Local Attention Res2Net with F0 Subband for Fake Speech Detection

Cunhang Fan, Jun Xue, Jianhua Tao +4

The rhythm of bonafide speech is often difficult to replicate, which causes that the fundamental frequency (F0) of synthetic speech is significantly different from that of real spe…

cs.SD2023★ 1 cited

Multi-perspective Information Fusion Res2Net with RandomSpecmix for Fake Speech Detection

Shunbo Dong, Jun Xue, Cunhang Fan +3

In this paper, we propose the multi-perspective information fusion (MPIF) Res2Net with random Specmix for fake speech detection (FSD). The main purpose of this system is to improve…