10 citations · 16 across the 8 of their papers we have counts for
8 papers
DAMOS: Learning Distortion-Aware Speech Quality Assessment through Explicit Distortion Localization
Naiyuan Li, Li Dong, Diqun Yan
Automatic speech quality assessment aims to predict Mean Opinion Scores (MOS) consistent with human subjective perception and is essential for evaluating speech generation, enhance…
Adversarial defense based on distribution transfer
Jiahao Chen, Diqun Yan, Li Dong
The presence of adversarial examples poses a significant threat to deep learning models and their applications. Existing defense methods provide certain resilience against adversar…
Universal Defensive Underpainting Patch: Making Your Text Invisible to Optical Character Recognition
JiaCheng Deng, Li Dong, Jiahao Chen +5
Optical Character Recognition (OCR) enables automatic text extraction from scanned or digitized text images, but it also makes it easy to pirate valuable or sensitive text from the…
Breaking Speaker Recognition with PaddingBack
Zhe Ye, Diqun Yan, Li Dong +1
Machine Learning as a Service (MLaaS) has gained popularity due to advancements in Deep Neural Networks (DNNs). However, untrusted third-party platforms have raised concerns about…
Fake the Real: Backdoor Attack on Deep Speech Classification via Voice Conversion
Zhe Ye, Terui Mao, Li Dong +1
Deep speech classification has achieved tremendous success and greatly promoted the emergence of many real-world applications. However, backdoor attacks present a new security thre…
SA: Sliding attack for synthetic speech detection with resistance to clipping and self-splicing
Deng JiaCheng, Dong Li, Yan Diqun +2
Deep neural networks are vulnerable to adversarial examples that mislead models with imperceptible perturbations. In audio, although adversarial examples have achieved incredible a…
Detecting and Recovering Adversarial Examples from Extracting Non-robust and Highly Predictive Adversarial Perturbations
Mingyu Dong, Jiahao Chen, Diqun Yan +3
Deep neural networks (DNNs) have been shown to be vulnerable against adversarial examples (AEs) which are maliciously designed to fool target models. The normal examples (NEs) adde…
Transferability of Adversarial Attacks on Synthetic Speech Detection
Jiacheng Deng, Shunyi Chen, Li Dong +2
Synthetic speech detection is one of the most important research problems in audio security. Meanwhile, deep neural networks are vulnerable to adversarial attacks. Therefore, we es…