most citedBSS-CFFMA: Cross-Domain Feature Fusion and Multi-Attention Speech Enhancement Network based on Self-Supervised Embedding

1 citations · 1 across the 4 of their papers we have counts for

collaborators

10 papers

cs.CV2025

FSDENet: A Frequency and Spatial Domains based Detail Enhancement Network for Remote Sensing Semantic Segmentation

Jiahao Fu, Yinfeng Yu, Liejun Wang

To fully leverage spatial information for remote sensing image segmentation and address semantic edge ambiguities caused by grayscale variations (e.g., shadows and low-contrast reg…

cs.CL2025

Argument-Centric Causal Intervention Method for Mitigating Bias in Cross-Document Event Coreference Resolution

Long Yao, Wenzhong Yang, Yabo Yin +5

Cross-document Event Coreference Resolution (CD-ECR) is a fundamental task in natural language processing (NLP) that seeks to determine whether event mentions across multiple docum…

cs.SD2025

AMNet: An Acoustic Model Network for Enhanced Mandarin Speech Synthesis

Yubing Cao, Yinfeng Yu, Yongming Li +1

This paper presents AMNet, an Acoustic Model Network designed to improve the performance of Mandarin speech synthesis by incorporating phrase structure annotation and local convolu…

cs.SD2025

Leveraging Label Potential for Enhanced Multimodal Emotion Recognition

Xuechun Shao, Yinfeng Yu, Liejun Wang

Multimodal emotion recognition (MER) seeks to integrate various modalities to predict emotional states accurately. However, most current research focuses solely on the fusion of au…

cs.SD2025

Magnitude-Phase Dual-Path Speech Enhancement Network based on Self-Supervised Embedding and Perceptual Contrast Stretch Boosting

Alimjan Mattursun, Liejun Wang, Yinfeng Yu +1

Speech self-supervised learning (SSL) has made great progress in various speech processing tasks, but there is still room for improvement in speech enhancement (SE). This paper pre…

cs.CL20241 cited

One Small and One Large for Document-level Event Argument Extraction

Jiaren Peng, Hongda Sun, Wenzhong Yang +3

Document-level Event Argument Extraction (EAE) faces two challenges due to increased input length: 1) difficulty in distinguishing semantic boundaries between events, and 2) interf…