Authors: Mahyar Abbasian, Iman Azimi, Mohammad Feli, Amir M. Rahmani, Ramesh Jain

Published on: May 08, 2024

Impact Score: 7.8

Arxiv code: Arxiv:2405.04777

Summary

• What is new: Introduces an LLM-based Conversational Health Agent (CHA) capable of interpreting and responding to users’ emotional states through multimodal cues.
• Why this is important: Current CHAs lack the ability to understand and respond to users’ emotional states effectively.
• What the research proposes: A new CHA leveraging the openCHA framework for rich, multimodal dialogue that recognizes and responds to various emotional tones.
• Results: High concordance between the CHA’s responses and human evaluators’ assessments, validating its empathic response capability.

Technical Details

Technological frameworks used: openCHA framework

Models used: Large Language Models (LLMs), Generative AI

Data used: Neutral prompts expressed in diverse emotional tones

Potential Impact

Healthcare sector, particularly mental health support services and digital health solutions providers.

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