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Customer Emotion-Aware Conversational Language Model using Generative AI and Retrieval-Augmented Generation (RAG)

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2025, 30(8), pp.103~110
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : June 20, 2025
  • Accepted : August 22, 2025
  • Published : August 29, 2025

Sung-Hyun Jee 1

1배화여자대학교

Accredited

ABSTRACT

Due to the development of artificial intelligence technology, conversational AI systems that understand and respond to human emotions are becoming increasingly important. While current AI assistants are being widely adopted across industries, technology that reflects human emotions and behaviors in conversations is still limited. This paper proposes a real-time conversational language model that considers the emotional state of the person conversing by utilizing RAG (Retrieval-Augmented Generation) technology, which is used to provide customized prompts. This research aims to infer human emotions based on analysis of text and tone that occur during conversations with people, and enable emotion-based customer response. The significance of this research lies in studying and applying AI technology that understands human emotions and behaviors.

Citation status

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