Research on emotionally intelligent dialogue generation based on automatic dialogue system
원문 초록
Automated dialogue systems are important applications of artificial intelligence, and traditional systems struggle to understand user emotions and provide empathetic feedback. This study integrates emotional intelligence technology into automated dialogue systems and creates a dialogue generation model with emotional intelligence through deep learning and natural language processing techniques. The model can detect and understand a wide range of emotions and specific pain signals in real time, enabling the system to provide empathetic interaction. By integrating the results of the study "Can artificial intelligence detect pain and express pain empathy?", the model's ability to understand the subtle elements of pain empathy has been enhanced, setting higher standards for emotional intelligence dialogue systems. The project aims to provide theoretical understanding and practical suggestions to integrate advanced emotional intelligence capabilities into dialogue systems, thereby improving user experience and interaction quality.
함께 살펴볼 논문
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SAGE: Steering and Refining Dialog Generation with State-Action Augmentation
ZipVoice-Dialog: Non-Autoregressive Spoken Dialogue Generation with Flow Matching
RLVER: Reinforcement Learning with Verifiable Emotion Rewards for Empathetic Agents
SDialog: A Python Toolkit for Synthetic Dialogue Generation and Analysis
Enhancing Medical Dialogue Generation through Knowledge Refinement and Dynamic Prompt Adjustment
EmoMeta: A Multimodal Dataset for Fine-grained Emotion Classification in Chinese Metaphors
토론
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