App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 9

Evidence-driven hybrid emotion state transition model for multimodal emotion recognition in conversation

Xu Chao
Zhang Yu
Sun Kaili
Pu Yue
School of Computer Science, Nanjing Audit University, Nanjing 211815, China
DOI: 10.19734/j.issn.1001-3695.2026.02.0021

Abstract

Multimodal conversational emotion recognition aims to predict the emotional state of each utterance in a dialogue by fusing information from multiple modalities, such as text, audio, and video. In this task, emotional states typically exhibit dynamic evolution characteristics, while information inconsistencies across modalities introduce significant interference, which jointly increases the complexity of emotion recognition. To address the above issues, this study proposes an evidence-driven hybrid emotion state transition model. This method fuses textual, acoustic and visual modalities to capture feature variations between adjacent utterances, and fuses intra-utterance local features with inter-utterance dynamic changes to construct evidence representations that reflect the intensity of emotional variation. Based on the obtained evidence representations, and combined with modality conflicts and speaker differences, the evidence representations guide a hybrid emotion state transition mechanism to adaptively regulate the two evolution patterns of continuity and abruptness. The model further combines the derived emotional states with dialogue context to complete utterance-level emotion prediction. Experimental results show that the proposed method achieves accuracies of 74.12% and 67.32%, and F1 scores of 74.03% and 66.11% on IEMOCAP and MELD, the benchmark datasets for multimodal conversational emotion recognition, which represents a significant improvement over existing baseline models.

Foundation Support

国家自然科学基金面上项目(62472227)
国家自然科学青年基金项目(62501289)
江苏省高校自然科学研究重大项目(24KJA520005)
江苏省高等学校自然科学研究面上项目(25KJB520020)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2026.02.0021
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 9

Publish History

[2026-05-26] Accepted Paper

Cite This Article

徐超, 张雨, 孙凯丽, 等. 一种基于证据驱动的多模态对话混合情绪状态转移模型 [J]. 计算机应用研究, 2026, 43 (9). (2026-06-02). https://doi.org/10.19734/j.issn.1001-3695.2026.02.0021. (Xu Chao, Zhang Yu, Sun Kaili, et al. Evidence-driven hybrid emotion state transition model for multimodal emotion recognition in conversation [J]. Application Research of Computers, 2026, 43 (9). (2026-06-02). https://doi.org/10.19734/j.issn.1001-3695.2026.02.0021. )

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  • Application Research of Computers Monthly Journal
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    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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