Annual Conference of KIPS (한국정보처리학회:학술대회논문집)

  • 2024.10a
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  • Pages.545-548
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  • 2024
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  • 2005-0011(pISSN)
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  • 2671-7298(eISSN)
Korea Information Processing Society (한국정보처리학회)
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A Review of Text Generation Models for Empathic Responses

  • Kim Ngan Phan (Department of AI Convergence, Chonnam National University) ;
  • Hyung-Jeong Yang (Department of AI Convergence, Chonnam National University) ;
  • Jieun Shin (Department of AI Convergence, Chonnam National University) ;
  • Seungwon Kim (Department of AI Convergence, Chonnam National University) ;
  • Soo-Hyung Kim (Department of AI Convergence, Chonnam National University)
  • Published : 2024.10.31
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Abstract

Empathetic response generation is a challenging concern in the field of natural language processing. Recent studies are trying to generate empathic responses to humans in dialogues. The published EmpatheticDialogues dataset is a solid foundation for the task of generating empathic responses. Many researchers have experimented with the EmpatheticDialogues dataset, which has many potential variations of transformer architectures. In this paper, we survey several previous approaches to the task of generating empathic responses with the aim of indicating the potential of future deep-learning models.

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Acknowledgement

This work was supported by the Institute of Information & Communications Technology Planning & Evaluation (IITP) under the Artificial Intelligence Convergence Innovation Human Resources Development (IITP-2023-RS-2023-00256629) grant funded by the Korea government (MSIT), the ITRC (Information Technology Research Center) support program (IITP-2024-RS-2024-00437718) supervised by IITP, and the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (RS- 2023-00219107).

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