7 citations · 8 across the 6 of their papers we have counts for
6 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…
Multi-Level Label Correction by Distilling Proximate Patterns for Semi-supervised Semantic Segmentation
Hui Xiao, Yuting Hong, Li Dong +5
Semi-supervised semantic segmentation relieves the reliance on large-scale labeled data by leveraging unlabeled data. Recent semi-supervised semantic segmentation approaches mainly…
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…
Facial Data Minimization: Shallow Model as Your Privacy Filter
Yuwen Pu, Jiahao Chen, Jiayu Pan +4
Face recognition service has been used in many fields and brings much convenience to people. However, once the user's facial data is transmitted to a service provider, the user wil…
EventTrojan: Manipulating Non-Intrusive Speech Quality Assessment via Imperceptible Events
Ying Ren, Kailai Shen, Zhe Ye +1
Non-Intrusive speech quality assessment (NISQA) has gained significant attention for predicting speech's mean opinion score (MOS) without requiring the reference speech. Researcher…
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…