35 citations · 67 across the 8 of their papers we have counts for
8 papers
SceneFake: An Initial Dataset and Benchmarks for Scene Fake Audio Detection
Jiangyan Yi, Chenglong Wang, Jianhua Tao +5
Many datasets have been designed to further the development of fake audio detection. However, fake utterances in previous datasets are mostly generated by altering timbre, prosody,…
An Initial Investigation for Detecting Vocoder Fingerprints of Fake Audio
Xinrui Yan, Jiangyan Yi, Jianhua Tao +5
Many effective attempts have been made for fake audio detection. However, they can only provide detection results but no countermeasures to curb this harm. For many related practic…
Fully Automated End-to-End Fake Audio Detection
Chenglong Wang, Jiangyan Yi, Jianhua Tao +6
The existing fake audio detection systems often rely on expert experience to design the acoustic features or manually design the hyperparameters of the network structure. However,…
CFAD: A Chinese Dataset for Fake Audio Detection
Haoxin Ma, Jiangyan Yi, Chenglong Wang +5
Fake audio detection is a growing concern and some relevant datasets have been designed for research. However, there is no standard public Chinese dataset under complex conditions.…
ADD 2022: the First Audio Deep Synthesis Detection Challenge
Jiangyan Yi, Ruibo Fu, Jianhua Tao +17
Audio deepfake detection is an emerging topic, which was included in the ASVspoof 2021. However, the recent shared tasks have not covered many real-life and challenging scenarios.…
Continual Learning for Fake Audio Detection
Haoxin Ma, Jiangyan Yi, Jianhua Tao +3
Fake audio attack becomes a major threat to the speaker verification system. Although current detection approaches have achieved promising results on dataset-specific scenarios, th…
Half-Truth: A Partially Fake Audio Detection Dataset
Jiangyan Yi, Ye Bai, Jianhua Tao +5
Diverse promising datasets have been designed to hold back the development of fake audio detection, such as ASVspoof databases. However, previous datasets ignore an attacking situa…
NavTuner: Learning a Scene-Sensitive Family of Navigation Policies
Haoxin Ma, Justin S. Smith, Patricio A. Vela
The advent of deep learning has inspired research into end-to-end learning for a variety of problem domains in robotics. For navigation, the resulting methods may not have the gene…