1 citations · 1 across the 4 of their papers we have counts for
6 papers
MIDAS: Mutual Information Disentanglement with Uncertainty-Aware Fusion for Incomplete Multimodal Sentiment Analysis
Yuhua Wen, Yingying Zhou, Qifei Li +4
Most existing multimodal sentiment analysis approaches assume access to complete multimodal inputs. However, real-world applications frequently encounter incomplete or corrupted mo…
DashFusion: Dual-stream Alignment with Hierarchical Bottleneck Fusion for Multimodal Sentiment Analysis
Yuhua Wen, Qifei Li, Yingying Zhou +4
Multimodal sentiment analysis (MSA) integrates various modalities, such as text, image, and audio, to provide a more comprehensive understanding of sentiment. However, effective MS…
Multi-Loss Learning for Speech Emotion Recognition with Energy-Adaptive Mixup and Frame-Level Attention
Cong Wang, Yizhong Geng, Yuhua Wen +7
Speech emotion recognition (SER) is an important technology in human-computer interaction. However, achieving high performance is challenging due to emotional complexity and scarce…
Deep Learning Approaches for Multimodal Intent Recognition: A Survey
Jingwei Zhao, Yuhua Wen, Qifei Li +8
Intent recognition aims to identify users' underlying intentions, traditionally focusing on text in natural language processing. With growing demands for natural human-computer int…
Psy-Insight: Explainable Multi-turn Bilingual Dataset for Mental Health Counseling
Keqi Chen, Zekai Sun, Yuhua Wen +3
The in-context learning capabilities of large language models (LLMs) show great potential in mental health support. However, the lack of counseling datasets, particularly in Chines…
Enhancing Modal Fusion by Alignment and Label Matching for Multimodal Emotion Recognition
Qifei Li, Yingming Gao, Yuhua Wen +2
To address the limitation in multimodal emotion recognition (MER) performance arising from inter-modal information fusion, we propose a novel MER framework based on multitask learn…