多模态情绪识别的全面审查:技术,挑战和未来方向
You Wu1, Qingwei Mi1, Tianhan Gao1
1Software College, Northeastern University, Shenyang 110169, China.
Biomimetics (Basel, Switzerland)
|July 25, 2025
概括
这篇评论探讨了多式联动情绪识别 (MER),将语音,视觉和文本数据整合起来,以进行强大的人类情绪分析. 灵感来自生物传感的MER系统,比单一模式的方法提供更高的准确性.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 生物医学工程 生物医学工程
背景情况:
- 人类的情绪是复杂的,经常通过多个感官道传递.
- 单模式情绪识别系统在捕捉微妙的情绪状态方面存在局限性.
- 仿生学为开发以生物原理为灵感的先进传感系统提供了一个框架.
研究的目的:
- 为多式联动情绪识别 (MER) 提供全面的审查.
- 将MER作为一种生物启发的传感范式.
- 突出MER领域的进步,挑战和未来方向.
主要方法:
- 审查有关MER系统的现有文献.
- 分析MER系统结构,特征提取和融合策略.
- 确定关键的挑战和未来的研究途径.
主要成果:
- MER系统集成了语音,视觉和文本数据,以进行更丰富的情感分析.
- 仿生学通过模拟人类多感官融合为MER提供了基础.
- 已经确定了MER的关键进展和里程碑.
结论:
- 比单模式方法,MER提供了比单模式方法更强大的情绪识别.
- 未来的MER研究应该专注于轻量级模型,跨体概括性,并纳入额外的模式.
- 提高准确性,可解释性和实用性对于现实世界MER应用至关重要.
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