4.7 Article

AI-Enabled Emotion Communication

Journal

IEEE NETWORK
Volume 33, Issue 6, Pages 15-21

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MNET.001.1900070

Keywords

Artificial intelligence; Robots; Emotion recognition; Cloud computing; Systems architecture; labeling

Funding

  1. National Key R&D Program of China [2018YFC1314600]
  2. Leading Initiative for Excellent Young Researcher (LEADER) of Ministry of Education, Culture, Sports, Science and Technology-Japan [16809746]
  3. Research Fund of State Key Laboratory of Marine Geology in Tongji University [MGK1803]
  4. Science and Technology Major Project of Hubei Province [2019AEA170]
  5. Research Fund of the Telecom-munications Advancement Foundation
  6. National Natural Science Foundation of China [61802139, 61672082, 61822101]
  7. Bei-jing Municipal Natural Science Foundation [4181002]

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With the development of AI technology, the application of AI will greatly change and influence people's daily lives. While AI technology brings great convenience to people's lives, people have shifted their focus from the physical world to the spiritual world, so there is an increasing demand for emotional services. As a result, emotional AI systems and emotional calculation are favored by many scholars nowadays. However, the existing emotional AI work mainly focuses on improving the accuracy of emotion recognition, lacking personalized emotional services for users. Therefore, in this article, the authors propose AI-EmoCom, which casts emotion as a communication medium in the network and makes the emotional communication system more intelligent by combining it with AI technology. We applied the AI-enabled emotional communication system to the field of unmanned driving, and proposed people-centered hybrid driving to reduce the incidence of traffic accidents to a greater extent. We also apply AI-enabled emotional communication to emotional social robots to provide users with personalized service emotion. Then the system architecture for the AI-enabled emotion communication is introduced in detail, and the no-tag learning model of dataset labeling and processing as well as the AI algorithm model for emotion recognition are elaborated in detail, and experiments are done to verify the interactive delay in the AI-enabled emotion communication system and accuracy of emotion recognition.

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