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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2404.11447 |
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| _version_ | 1866916226288058368 |
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| author | Wang, Jin Wang, JinFei Dai, Shuying Yu, Jiqiang Li, Keqin |
| author_facet | Wang, Jin Wang, JinFei Dai, Shuying Yu, Jiqiang Li, Keqin |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_11447 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Research on emotionally intelligent dialogue generation based on automatic dialogue system Wang, Jin Wang, JinFei Dai, Shuying Yu, Jiqiang Li, Keqin Artificial Intelligence Computation and Language 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. |
| title | Research on emotionally intelligent dialogue generation based on automatic dialogue system |
| topic | Artificial Intelligence Computation and Language |
| url | https://arxiv.org/abs/2404.11447 |