Software Technology Research
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 10
3100-3106

Consistency based graph convolution network for multimodal emotion recognition in conversation

Tan Xiaoconga
Guo Junjuna,b
Xian Yantuana,b
Xiang Yana,b
a. Faculty of Information Engineering & Automation, b. Yunnan Key Laboratory of Artificial Intelligence, Kunming University of Science & Technology, Kunming 650500, China
DOI: 10.19734/j.issn.1001-3695.2023.02.0064

Abstract

Multimodal emotion recognition in conversations(MERC) is a task to predict the emotional category of the discourse in a dialogue based on its textual, audio, and visual modality. Existing studies focus on multimodal feature extraction and fusion of discourse context without fully considering the utilization of emotional features of different speakers. Therefore, this paper proposed a model of multimodal dialogue emotion recognition based on a consistent graph convolutional network. The model first constructed a graph convolutional network of multimodal feature learning and fusion, and obtained the context features of each discourse. On this basis, the average features of the speaker in the complete dialogue as the constraint to make the model learn more reasonable discourse features, so as to improve the performance of predicting emotion class. The paper compared with other baseline models on two benchmark datasets IEMOCAP and MELD. And the results show that the proposed model is superior to the other models. In addition, the paper verifies the consistency constraints and other components of the model through ablation experiments.

Foundation Support

国家自然科学基金地区项目(62162037)
云南省科技厅面上项目(202001AT070047,202001AT070046)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.02.0064
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 10
Section: Software Technology Research
Pages: 3100-3106
Serial Number: 1001-3695(2023)10-033-3100-07

Publish History

[2023-05-11] Accepted Paper
[2023-10-05] Printed Article

Cite This Article

谭晓聪, 郭军军, 线岩团, 等. 基于一致性图卷积模型的多模态对话情绪识别 [J]. 计算机应用研究, 2023, 40 (10): 3100-3106. (Tan Xiaocong, Guo Junjun, Xian Yantuan, et al. Consistency based graph convolution network for multimodal emotion recognition in conversation [J]. Application Research of Computers, 2023, 40 (10): 3100-3106. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    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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