大连理工大学学报2025，Vol.65Issue(3)：313-320,8.DOI:10.7511/dllgxb202503013
融合情绪标签和原型网络的对话情绪识别
Emotion recognition in conversation integrating emotion labels and prototypical networks
摘要
Abstract
The goal of emotion recognition in conversation is to identify the emotions of the utterances within a dialogue.Although several advanced supervised contrastive learning methods have been proposed to distinguish different emotion categories,the intrinsic information in emotion labels is not fully utilized.Emotion labels contain specific semantics and complex relationships.They can be utilized as samples for contrastive learning to facilitate emotion recognition.A label-guided prototypical contrastive learning method is proposed for emotion recognition in conversation.This method designs a contrastive objective in which the emotion labels are treated as positive/negative samples and the constructed label embeddings are involved in the contrastive training process,which effectively enriches the contrastive samples.Additionally,this method utilizes a prototypical network to focus on the overall distribution and average characteristics of the data.Experiments on three widely used benchmark datasets show that the proposed method outperforms existing approaches for emotion recognition in conversation.关键词
情绪识别/对比学习/标签信息/原型网络Key words
emotion recognition/contrastive learning/label information/prototypical network分类
计算机与自动化引用本文复制引用
张洪通,王健,徐博,杨亮,林鸿飞..融合情绪标签和原型网络的对话情绪识别[J].大连理工大学学报,2025,65(3):313-320,8.基金项目
国家自然科学基金资助项目(62006034). （62006034）
