智能科学与技术学报2024，Vol.6Issue(1)：76-87,12.DOI:10.11959/j.issn.2096-6652.202401
基于集成学习与聚类联合标注的多模态个体情绪识别
Multimodal individual emotion recognition with joint labeling based on integrated learning and clustering
摘要
Abstract
To address the low recognition accuracy of generic emotion recognition models when faced with different indi-viduals,a multimodal individual emotion recognition technique based on joint labelling with integrated learning and clus-tering was proposed.The method first trained a generic emotion recognition model based on a public dataset,then anal-lysed the distributional differences between the data in the public dataset and the unlabelled data of individuals,and estab-lished a cross-domain model for predicting and labelling pseudo-labels of individual data.At the same time,the individual data were weighted clustered and labelled with cluster labels,and the cluster labels were used to jointly label with pseudo-labels,and high confidence samples were screened to further train the generic model to obtain a personalized emotion rec-ognition model.Using this method to annotate these data with the experimentally collected data of 3 emotions from 3 sub-jects,the final optimized personalized model achieved an average recognition accuracy of more than 80%for the 3 emo-tions,which was at least a 35%improvement compared to the original generic model.关键词
个体情绪识别/领域自适应/集成学习/聚类/联合标注Key words
individual emotion recognition/domain adaptation/integrated learning/clustering/joint annotation分类
信息技术与安全科学引用本文复制引用
柯善军,聂成洋,王钰苗,何邦胜..基于集成学习与聚类联合标注的多模态个体情绪识别[J].智能科学与技术学报,2024,6(1):76-87,12.基金项目
重庆市教委科学技术研究项目(No.2020CJZ053)The Scientific and Technological Research Program of Chongqing Municipal Education Commission(No.2020CJZ053) （No.2020CJZ053）
