Research on Intention Recognition and Security of Multimodal Human-Computer Interaction System Based on Deep Learning

Ge Zhang

2025

Abstract

With the development of science and technology in recent years, human-computer interaction systems are developing in a more natural, efficient and safer direction, and the scenarios of human-computer interaction are becoming increasingly complex. However, traditional interaction systems that rely on a single modality (such as voice or vision) have gradually exposed problems such as low security, insufficient robustness and incomplete understanding of user intent in multimodal data processing, and can no longer support the needs of modern more immersive and intelligent interaction systems. This paper studies the typical applications of single modality in human-computer interaction systems, and deeply analyzes its limitations and potential safety hazards exposed in complex interactive environments. Based on this, this paper further explore multimodal interaction based on deep learning, especially the key role of convolutional neural networks (CNN) and recurrent neural networks (RNN) in user intent recognition, to provide certain theoretical support and reference for building a safer and more intelligent human-computer interaction system.

Paper Citation

in Harvard Style

Zhang G. (2025). Research on Intention Recognition and Security of Multimodal Human-Computer Interaction System Based on Deep Learning. In Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI; ISBN 978-989-758-792-4, SciTePress, pages 394-398. DOI: 10.5220/0014360200004718

in Bibtex Style

@conference{emiti25,
author={Ge Zhang},
title={Research on Intention Recognition and Security of Multimodal Human-Computer Interaction System Based on Deep Learning},
booktitle={Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI},
year={2025},
pages={394-398},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0014360200004718},
isbn={978-989-758-792-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI
TI - Research on Intention Recognition and Security of Multimodal Human-Computer Interaction System Based on Deep Learning
SN - 978-989-758-792-4
AU - Zhang G.
PY - 2025
SP - 394
EP - 398
DO - 10.5220/0014360200004718
PB - SciTePress