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App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 2

Progressive information fusion for emotional dialogue generation based on bart

Tang Zehui1a
Miu Yuqing1a,1b
Liu Tonglai2
Zhang Wanzhen2
Zhou Ming3
1. a. School of Computer Science & Information Security, b. Guangxi Key Laboratory of Image & Graphics Intelligent Processing, Guilin University of Electronic Technology, Guilin Guangxi 541004, China
2. College of artificial intelligence, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China
3. Guilin Hivision Technology Company, Guilin Guangxi 541004, China
DOI: 10.19734/j.issn.1001-3695.2025.07.0240

Abstract

Current emotional dialogue generation models have not fully exploited external knowledge to support emotion classification and suffer from redundant knowledge extraction. A progressive information fusion model based on BART was proposed to address these issues. The model adopted the BART framework for encoding and decoding, and gradually filtered relevant knowledge in two stages of emotion classification and dialogue generation. In the classification stage, a knowledge-aware fusion module was constructed by introducing multi-head attention and gating mechanisms, which selected context-related knowledge to assist emotion classification. In the generation stage, a knowledge scoring strategy was designed to calculate dynamic gradient corrections according to the classification results. A knowledge refinement fusion module was then built to adjust knowledge weights related to contextual cognition, further filtering knowledge consistent with dialogue emotions. Knowledge and contextual representations were fused to generate responses, alleviating redundancy in knowledge extraction. Experiments on public dialogue datasets demonstrated that the proposed model outperformed existing methods on multiple evaluation metrics. The results confirm that the model is effective.

Foundation Support

国家自然科学基金资助项目(62366010,62366011)
广东省研究生教育创新计划项目(2023A1515011230)
桂林电子科技大学研究生教育创新计划资助项目(2025YCXS076)
广东省哲学社会科学规划专项项目(GD25CW04)
广东省哲学社会科学规划2025年度潮州文化研究专项(GD25CW04)
2025年广东省本科高校"外语教学改革研究与实践"专项课题拟立项名单(25GWYB08)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.07.0240
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 2

Publish History

[2025-10-27] Accepted Paper

Cite This Article

汤泽辉, 缪裕青, 刘同来, 等. 基于BART的渐进式信息融合的情感对话生成 [J]. 计算机应用研究, 2026, 43 (2). (2025-11-04). https://doi.org/10.19734/j.issn.1001-3695.2025.07.0240. (Tang Zehui, Miu Yuqing, Liu Tonglai, et al. Progressive information fusion for emotional dialogue generation based on bart [J]. Application Research of Computers, 2026, 43 (2). (2025-11-04). https://doi.org/10.19734/j.issn.1001-3695.2025.07.0240. )

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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