1 citations · 1 across the 9 of their papers we have counts for
9 papers
RTCFake: Speech Deepfake Detection in Real-Time Communication
Jun Xue, Zhuolin Yi, Yihuan Huang +6
With the rapid advancement of speech generation technologies, the threat posed by speech deepfakes in real-time communication (RTC) scenarios has intensified. However, existing det…
Unifying Speech Editing Detection and Content Localization via Prior-Enhanced Audio LLMs
Jun Xue, Yi Chai, Yanzhen Ren +6
Existing speech editing detection (SED) datasets are predominantly constructed using manual splicing or limited editing operations, resulting in restricted diversity and poor cover…
ALLM4ADD: Unlocking the Capabilities of Audio Large Language Models for Audio Deepfake Detection
Hao Gu, Jiangyan Yi, Chenglong Wang +6
Audio deepfake detection (ADD) has grown increasingly important due to the rise of high-fidelity audio generative models and their potential for misuse. Given that audio large lang…
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…
Reject Threshold Adaptation for Open-Set Model Attribution of Deepfake Audio
Xinrui Yan, Jiangyan Yi, Jianhua Tao +6
Open environment oriented open set model attribution of deepfake audio is an emerging research topic, aiming to identify the generation models of deepfake audio. Most previous work…
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…
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…