一个无线,无电池的人工喉贴片,具有深度学习,用于情绪语音识别
Bingxin Xu1, Guanming Lin1, Xiaohui Hong1
1Guangdong Provincial Key Laboratory of Sensor Technology and Biomedical Instrument, School of Biomedical Engineering, Shenzhen Campus of Sun Yat-Sen University, Shenzhen, China.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
|January 28, 2026
概括
这项研究介绍了一种无线,无电池的人工喉贴片系统 (ATPS),该系统使用深度学习来识别语音和情绪. 这项创新增强了声障碍患者的沟通能力,提供了更先进和个性化的解决方案.
科学领域:
- 生物医学工程 生物医学工程
- 人工智能的人工智能
- 可穿戴技术可穿戴技术
背景情况:
- 目前用于声障碍的语音启用技术往往受到绳索,体积和缺乏情感识别的限制.
- 解决这些局限性对于改善受影响个人的通信可访问性和生活质量至关重要.
研究的目的:
- 开发一种无线,无电池的人工喉贴片系统 (ATPS),能够同时识别语音和情绪.
- 克服现有的辅助通信技术的实际部署挑战.
主要方法:
- 在ATPS中集成基于碳纳米管的薄膜应变传感器和小型化的柔性印刷电路板 (FPCB).
- 使用智能手机连接的系统与近场通信 (NFC) 实时信号传输.
- 实施混合深度学习架构,从传感器数据中提取语音和情感信息.
主要成果:
- 证明了成功的实时传感和无线传输喉信号.
- 使用ATPS和深度学习实现了准确的同时识别语音和情绪.
- 验证了传感器读数对于情感识别的充分性.
结论:
- 开发的ATPS为语音和情绪识别提供了一个无线,无电池的解决方案,大大推进了辅助通信.
- 这项技术扩展了声障碍患者的沟通工具,并使个性化临床应用成为可能.
- 该系统代表了朝着更自然和富有表现力的沟通迈出的重要一步,对于那些无法使用传统语言的人来说.
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