DiagESC: Dialogue Synthesis for Integrating Depression Diagnosis into Emotional Support Conversation

Seungyeon Seo, Gary Geunbae Lee
8/12/2024
cs.CL

No official code found. Best implementation: seungyeon-seo/DiagESC (9 stars, last commit 2024-05-23).

Abstract

Dialogue systems for mental health care aim to provide appropriate support to individuals experiencing mental distress. While extensive research has been conducted to deliver adequate emotional support, existing studies cannot identify individuals who require professional medical intervention and cannot offer suitable guidance. We introduce the Diagnostic Emotional Support Conversation task for an advanced mental health management system. We develop the DESC dataset to assess depression symptoms while maintaining user experience by utilizing task-specific utterance generation prompts and a strict filtering algorithm. Evaluations by professional psychological counselors indicate that DESC has a superior ability to diagnose depression than existing data. Additionally, conversational quality evaluation reveals that DESC maintains fluent, consistent, and coherent dialogues.

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seungyeon-seo/DiagESCCommunity100%
90May 18, 20242 years ago

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Cite this paper

@article{seo2024diagesc,
  title  = {DiagESC: Dialogue Synthesis for Integrating Depression Diagnosis into Emotional Support Conversation},
  author = {Seungyeon Seo and Gary Geunbae Lee},
  year   = {2024},
  eprint = {2408.06044},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2408.06044v1}
}

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