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Special Topics in Multimodal Fusion
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App. Res. of Comp. Printed Article
Vol. 42, 2025 No. 9
2590-2598

Multimodal dialogue model and applications based on modality-sensitive attention mechanism

Du Wei1
Zhu Xiaoying2a
Xu Fangmin2b
Zheng Jiansheng3
Zhu Fuxi1
Gong Mingmin1
Li Ziyu1
1. School of Information Engineering, Wuhan College, Wuhan 430212, China
2. a. School of Cyberspace Security, b. School of Information and Communication Engineering, Beijing University of Posts & Telecommunications, Beijing 100876, China
3. School of Electronic Information, Wuhan University, Wuhan 430072, China
DOI: 10.19734/j.issn.1001-3695.2025.02.0043

Abstract

The multimodal dialogue system adopts methods such as Transformer, cross-attention mechanism and pre-trained models to fuse text, speech and video modalities of different granularities and extracts cross-modal features. However, the existing research ignores the sensitive differences of different modal features on classification tasks, resulting in excessive fusion and information redundancy. Regarding the influence of sequential features of multimodal fusion on classification results, this paper proposed the multimodal dialogue model MDM-MSAM(multimodal dialogue model based on modality sensitive attention mechanism). The model was divided into three parts: master-slave mode screening, dual-modal cross-modal fusion, and trimodal cross-modal fusion. By determining the master-slave modalities and extracting cross-dual-modal features, the model re-fused them with the tri-modal fusion features, then formed the modality-sensitive hierarchical cross-multimodal features. The classification accuracy on MintRec and CMU-MOSI datasets increase by 3.15% and 3.5% respectively compared with the currently best-performing model. The deployment and application of the MDM-MSAM in flow engine-based multi-round dialogue system achieve good application results.

Foundation Support

国家自然科学基金资助项目(42374013)
北京市自然科学基金资助项目(L234080)
武汉学院科研基金年度计划资助项目(JJA202304)
中国高校产学研创新基金—腾讯科技创新教育专项资助项目(2022TX007)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.02.0043
Publish at: Application Research of Computers Printed Article, Vol. 42, 2025 No. 9
Section: Special Topics in Multimodal Fusion
Pages: 2590-2598
Serial Number: 1001-3695(2025)09-004-2590-09

Publish History

[2025-05-21] Accepted Paper
[2025-09-05] Printed Article

Cite This Article

杜维, 朱晓瑛, 许方敏, 等. 基于模态敏感注意力机制的多模态对话模型及应用 [J]. 计算机应用研究, 2025, 42 (9): 2590-2598. (Du Wei, Zhu Xiaoying, Xu Fangmin, et al. Multimodal dialogue model and applications based on modality-sensitive attention mechanism [J]. Application Research of Computers, 2025, 42 (9): 2590-2598. )

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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