用多模态深度学习让界面读懂用户情绪，实现更贴心的交互。
Emotion-Aware Interaction Design in Intelligent User Interface Using Multi-Modal Deep Learning
- 融合表情、语音和文本信息，用多分支Transformer实时识别情绪。
- 在MELD数据集上准确率和F1分数显著优于传统方法。
- 适合做情感化交互、人机共情设计的研究与开发人员参考。
在人机交互无处不在的时代，用户界面（UI）设计的重要性不言而喻。优秀的UI不仅能提升易用性，还能创造更自然、直观且富有情感吸引力的体验，使技术在日常生活中更具可及性与影响力。本研究针对这一需求，提出一种先进的情绪识别系统，显著提升界面的情感响应能力。通过多分支Transformer模型融合面部表情、语音与文本数据，系统可实时解析复杂的情绪线索，使界面能更共情、高效地与用户互动。基于公开的MELD数据集验证，所提模型在情绪识别准确率与F1分数上均实现显著提升，超越传统方法。结果表明，先进的情绪识别技术对推动UI演进至关重要，使技术更贴近用户需求与情绪状态。本研究强调，增强界面的情感智能不仅是技术革新，更是构建用户与数字世界深层、有意义连接的关键，最终重塑人们日常使用技术的方式。
原文摘要 · Abstract (English)
In an era where user interaction with technology is ubiquitous, the importance of user interface (UI) design cannot be overstated. A well-designed UI not only enhances usability but also fosters more natural, intuitive, and emotionally engaging experiences, making technology more accessible and impactful in everyday life. This research addresses this growing need by introducing an advanced emotion recognition system to significantly improve the emotional responsiveness of UI. By integrating facial expressions, speech, and textual data through a multi-branch Transformer model, the system interprets complex emotional cues in real-time, enabling UIs to interact more empathetically and effectively with users. Using the public MELD dataset for validation, our model demonstrates substantial improvements in emotion recognition accuracy and F1 scores, outperforming traditional methods. These findings underscore the critical role that sophisticated emotion recognition plays in the evolution of UIs, making technology more attuned to user needs and emotions. This study highlights how enhanced emotional intelligence in UIs is not only about technical innovation but also about fostering deeper, more meaningful connections between users and the digital world, ultimately shaping how people interact with technology in their daily lives.
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