使用机器学习辅助的可穿戴感应激活系统,在没有声的情况下说话
Ziyuan Che1, Xiao Wan1, Jing Xu1
1Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
Nature communications
|March 13, 2024
概括
这项研究引入了一种软磁弹性可穿戴系统,用于辅助说话,绕过声功能障碍. 这项技术准确地将肌肉运动转化为语音,帮助患有语音障碍的患者.
科学领域:
- 生物医学工程 生物医学工程
- 材料科学 材料科学 材料科学
- 语音科学 语言科学
背景情况:
- 听力障碍或语音障碍通常是由于病态的声状况或从喉癌中术后恢复引起的.
- 现有的语音辅助技术通常在模仿自然语音产生方面存在局限性,或需要侵入性程序.
研究的目的:
- 开发一种自动供电,可穿戴的感觉激活系统,用于辅助语音.
- 为了使有声功能障碍的个体能够有效地沟通,而不依赖声振动.
主要方法:
- 一个柔软的磁弹性可穿戴系统被设计成一个轻量级 (约. 7.2 g),类似皮肤的模量 (7.83 × 10^5 Pa) 和高伸展性 (164%).
- 该系统的传感元件捕获了喉外界肌肉运动,并将其转化为电信号.
- 机器学习算法将这些信号高精度地转化为语音,执行组件生成语音信号.
主要成果:
- 可穿戴系统表现出对皮肤出汗的稳定性.
- 传感组件实现了对喉肌肉活动的高准确度信号捕获.
- 使用机器学习的语音翻译实现了94.68%的准确性.
结论:
- 开发的软磁弹性可穿戴系统为发言提供了不依赖声振动的语音生产.
- 这项技术有可能恢复失声症患者的语音功能.
- 该系统可以显著提高声损伤的个体的生活质量.
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