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Smart Beaker Based on Multimodal Fusion and Intentional Understanding
Author(s) -
Di Dong,
Zhiquan Feng,
Jinglan Tian
Publication year - 2020
Publication title -
proceedings of 2020 the 6th international conference on computing and data engineering
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/3379247.3379257
Subject(s) - interactivity , computer science , usability , modal , sensor fusion , feature extraction , modality (human–computer interaction) , suite , human–computer interaction , artificial intelligence , multimedia , archaeology , history , chemistry , polymer chemistry
In the current simulation experiment system, the experimental design of single mode is less interactive and less accurate. In order to solve this problem, this paper proposes an experimental interaction kit based on sound and sensor, and designs a multi-modal fusion and intent understanding algorithm. Firstly, the method of multi-sensor signal extraction and speech feature extraction is introduced. Then, based on the results obtained by the two methods, an algorithm based on decision-level fusion is studied, which solves the problem of perception of user's operation intention in virtual chemistry experiments. Finally, the usability of the multimodal intent understanding algorithm proposed in this paper is verified by designing a complete chemical experiment system. Experiments show that the multi-modal intent understanding algorithm based on sensor and speech input is due to a single modality in terms of interactivity and accuracy, and the physical interaction suite designed in this paper greatly improves the intelligence and interactivity of the system.

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