Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 6
1778-1783

Multi-turn emotion dialogue generation model based on dual-decoder

Luo Hong1
Lu Haijun1
Chen Juanjuan2
Shen Yujie2
Wang Dan2
1. China Mobile Hangzhou Information Technology Co. , Ltd. , Hangzhou 310000, China
2. State Key Laboratory of Integrated Services Networks, Xidian University, Xi'an 710071, China
DOI: 10.19734/j.issn.1001-3695.2023.10.0519

Abstract

The success of emotional dialogue systems relies on the ability to comprehend, perceive, and express emotions, while facial expressions and personality can also help. However, despite the crucial importance of this multi-modal information in multi-turn emotional dialogues, existing systems still need to be improved to leverage multi-modal information's advantages and overlook the significance of contextual relevance. To address this issue, this paper proposed a multi-turn emotional dialogue generation model based on a dua-decoding method(MEDG-DD). The model utilized a heterogeneous graph neural network encoder to integrate historical dialogue, facial expressions, emotion flow, and speaker information, obtaining a more comprehensive dialogue context. Subsequently, it employed a dual-decoding mechanism based on attention to generate emotionally rich expressions relevant to the dialogue context. Experimental results demonstrate that the proposed model effectively integrates multi-modal information, achieving more accurate, natural, and coherent emotional expressions. Compared to the traditional ReCoSa model, this model exhibits significant improvements across various evaluation metrics.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.10.0519
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 6
Section: Algorithm Research & Explore
Pages: 1778-1783
Serial Number: 1001-3695(2024)06-025-1778-06

Publish History

[2024-01-15] Accepted Paper
[2024-06-05] Printed Article

Cite This Article

罗红, 陆海俊, 陈娟娟, 等. 基于双层解码的多轮情感对话生成模型 [J]. 计算机应用研究, 2024, 41 (6): 1778-1783. (Luo Hong, Lu Haijun, Chen Juanjuan, et al. Multi-turn emotion dialogue generation model based on dual-decoder [J]. Application Research of Computers, 2024, 41 (6): 1778-1783. )

About the Journal

  • 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.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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