计算机应用与软件2025，Vol.42Issue(9)：156-164,9.DOI:10.3969/j.issn.1000-386x.2025.09.021
基于信息增强多头注意力的多模态情感分析
MULTIMODAL SENTIMENT ANALYSIS BASED ON INFORMATION ENHANCED MULTI-HEAD ATTENTION
摘要
Abstract
Aimed at some problems in multimodal sentiment analysis methods,such as equal treatment of different modal features,insufficient mining and fusion of information carried by each modal,and low accuracy of sentiment classification,a multimodal sentiment analysis model based on information enhanced multi-head attention is proposed.We used multi-task learning to mine the shared semantics of other two non-text features(speech features and visual features)relative to text features,and enhanced the representation of text emotion features.Moreover,since the interaction information of any two models made different contributions to the final sentiment prediction,we designed a multi-head attention fusion network,which could effectively fuse the effective information carried by different model through the reasonable allocation of speech-text,visual-text and speech-visual features.The experimental results show that the performance of the model in multimodal emotion classification tasks is better than the existing methods.关键词
多模态情感分析/多任务学习/共享语义/多模态融合/多头注意力机制Key words
Multimodal sentiment analysis/Multi-task learning/Shared semantics/Multimodal fusion/Multi-head attention mechanism分类
信息技术与安全科学引用本文复制引用
张换香,刘璐瑶,张景,惠丽峰..基于信息增强多头注意力的多模态情感分析[J].计算机应用与软件,2025,42(9):156-164,9.基金项目
国家自然科学基金项目(61562065) （61562065）
内蒙古自然科学基金项目(2019MS06001). （2019MS06001）
