Multimodal Emotion Recognition in Conversations: A Survey of Methods, Trends, Challenges and Prospects
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908526242168832 |
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| author | Wu, Chengyan Cai, Yiqiang Liu, Yang Zhu, Pengxu Xue, Yun Gong, Ziwei Hirschberg, Julia Ma, Bolei |
| author_facet | Wu, Chengyan Cai, Yiqiang Liu, Yang Zhu, Pengxu Xue, Yun Gong, Ziwei Hirschberg, Julia Ma, Bolei |
| contents | While text-based emotion recognition methods have achieved notable success, real-world dialogue systems often demand a more nuanced emotional understanding than any single modality can offer. Multimodal Emotion Recognition in Conversations (MERC) has thus emerged as a crucial direction for enhancing the naturalness and emotional understanding of human-computer interaction. Its goal is to accurately recognize emotions by integrating information from various modalities such as text, speech, and visual signals.
This survey offers a systematic overview of MERC, including its motivations, core tasks, representative methods, and evaluation strategies. We further examine recent trends, highlight key challenges, and outline future directions. As interest in emotionally intelligent systems grows, this survey provides timely guidance for advancing MERC research. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_20511 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Multimodal Emotion Recognition in Conversations: A Survey of Methods, Trends, Challenges and Prospects Wu, Chengyan Cai, Yiqiang Liu, Yang Zhu, Pengxu Xue, Yun Gong, Ziwei Hirschberg, Julia Ma, Bolei Computation and Language While text-based emotion recognition methods have achieved notable success, real-world dialogue systems often demand a more nuanced emotional understanding than any single modality can offer. Multimodal Emotion Recognition in Conversations (MERC) has thus emerged as a crucial direction for enhancing the naturalness and emotional understanding of human-computer interaction. Its goal is to accurately recognize emotions by integrating information from various modalities such as text, speech, and visual signals. This survey offers a systematic overview of MERC, including its motivations, core tasks, representative methods, and evaluation strategies. We further examine recent trends, highlight key challenges, and outline future directions. As interest in emotionally intelligent systems grows, this survey provides timely guidance for advancing MERC research. |
| title | Multimodal Emotion Recognition in Conversations: A Survey of Methods, Trends, Challenges and Prospects |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2505.20511 |