Emotion-Aided Semantic Communication System for Reliable Semantic Recovery Under Low SNR

The vision for sixth generation wireless communication entails an intelligent and personalized communication scheme that addresses individual needs. To accomplish this, semantic communication with the help of machine learning and natural language processing technologies can play a crucial role. Howe...

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Bibliographic Details
Published in:IEEE communications letters 2024-03, Vol.28 (3), p.503-507
Main Authors: Luo, Peng, Zhao, Haitao, Cao, Kuo, Liu, Yueling, Zhang, Yuyuan, Wei, Jibo
Format: Article
Language:English
Subjects:
Comets
Communications systems
Customization
Decoding
emotion
Emotion recognition
Emotions
Knowledge bases (artificial intelligence)
Machine learning
Natural language processing
personalized communication
Recovery
Semantic communications
Semantics
Signal to noise ratio
Training
Transformers
Wireless communications
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Summary:The vision for sixth generation wireless communication entails an intelligent and personalized communication scheme that addresses individual needs. To accomplish this, semantic communication with the help of machine learning and natural language processing technologies can play a crucial role. However, existing semantic communication systems fail to model the interaction between semantics and emotion, which is vital for personalized communication. This letter proposes an emotion-aided semantic communication system that utilizes an external knowledge base for emotion extraction at the transmitter and adopts emotion recognition and selection at the receiver for semantic recovery. Simulation results demonstrate the effectiveness of incorporating emotional knowledge into semantic communication, especially in the low signal-to-noise ratio (SNR) region.
ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2024.3352559