情感识别大模型研究综述OA
Research Survey on Emotion Recognition Large Language Models
近年来,大模型技术的迅速发展为情感识别提供了全新的研究范式.相较于传统方法,情感识别大模型在复杂场景理解、零/少样本泛化以及多模态协同表征等方面展现出显著优势.围绕情感识别大模型研究展开了系统性综述与分析.对单模态情感识别的大模型研究进行梳理,按照模态类型分别总结文本、语音、视觉与生理信号等方向的进展与特点.聚焦多模态情感识别,依据多源信息融合的技术路径,将现有方法归纳为统一编码器架构、层次化融合架构与生成式模型架构,并对其设计理念、关键技术与适用场景进行比较评述.进一步地,从提升识别精度、增强泛化能力与优化多模态融合等维度综合分析最新研究进展,强调大模型技术在情感识别领域的重要作用与应用潜力.指出当前研究仍面临情感时序建模能力不足、跨文化认知偏差等挑战,并据此提出增强模型长程时序建模能力以及建立多模态文化情感基准体系等未来研究方向.
The rapid development of large language models offers a new paradigm for emotion recognition,demonstrating significant advantages over conventional methods in complex scenario understanding,zero/few-shot generalization,and multimodal collaborative representation.This paper provides a systematic review of large-scale emotion recognition models.It first summarizes advances in unimodal emotion recognition across text,speech,visual,and physiological signals.The study then focuses on multimodal approaches,categorizing them into unified encoder architectures,hierarchical fusion architectures,and generative model architectures based on fusion strategies,and compares their design principles,key techniques,and applicable scenarios.Further analysis highlights improvements in recognition accuracy,generalization ca-pability,and multimodal fusion,underscoring the important role and potential of large language models in this field.Finally,this paper identifies challenges such as insufficient temporal emotion modeling and cross-cultural cognitive biases,and suggests future directions including enhancing long-range temporal modeling and establishing multimodal cultural emo-tion benchmarks.
吴敖;王海龙;柳林;史文韬
内蒙古师范大学 计算机科学技术学院,呼和浩特 010022||内蒙古师范大学 计算机科学联合创新实验室,呼和浩特 010022内蒙古师范大学 计算机科学技术学院,呼和浩特 010022||内蒙古师范大学 计算机科学联合创新实验室,呼和浩特 010022||内蒙古师范大学 科学技术史研究院,呼和浩特 010022内蒙古师范大学 计算机科学技术学院,呼和浩特 010022||内蒙古师范大学 计算机科学联合创新实验室,呼和浩特 010022内蒙古师范大学 计算机科学技术学院,呼和浩特 010022||内蒙古师范大学 计算机科学联合创新实验室,呼和浩特 010022
信息技术与安全科学
单模态情感识别多模态情感识别多源信息融合大模型技术
unimodal emotion recognitionmultimodal emotion recognitionmulti-source information fusionlarge lan-guage model technology
《计算机科学与探索》 2026 (3)
625-649,25
国家自然科学基金(62566047)内蒙古自治区自然科学基金(2023LHMS06006,2024LHMS06015)内蒙古师范大学基本科研业务费专项资金(2022JBYJ032)内蒙古自治区档案馆档案科技项目(2023-13)无穷维哈密顿系统及其算法应用教育部重点实验室(内蒙古师范大学)开放课题(2023KFYB03)2022年度国家社科基金冷门绝学研究专项学术团队项目(22VJXT008).This work was supported by the National Natural Science Foundation of China(62566047),the Natural Science Foundation of Inner Mongolia(2023LHMS06006,2024LHMS06015),the Fundamental Research Funds for Inner Mongolia Normal University(2022JBYJ032),the Archives Science Project of Inner Mongolia(2023-13),the Project of Key Laboratory of Infinite-Dimensional Ham-iltonian System and Its Algorithm Application(Inner Mongolia Normal University),Ministry of Education(2023KFYB03),and the 2022 Academic Team Project of the National Social Science Fund of China Special Program for Endangered and Obscure Disciplines(22VJXT008).
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