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灵活的自动供电低分贝语音识别面具

Jianing Li¹, Yating Shi¹, Jianfeng Chen¹

¹Department of Physics, College of Physical Science and Technology, Research Institution for Biomimetics and Soft Matter, Xiamen University, Xiamen 361005, China.

Sensors (Basel, Switzerland)

|May 25, 2024

概括

一个新的面具集成的 triboelectric 纳米发电机 (TENG) 通过空气流振动捕获语音. 这使得在安静的环境中能够进行准确,谨慎的通信和扬声器识别.

科学领域:

收集能源收集能源
可穿戴传感器穿戴式传感器
信号处理信号处理

背景情况:

在图书馆和会议室等环境中,沉默的沟通至关重要.
现有的对离散相互作用的方法是有限的.
需要一种不引人注目的语音捕捉技术.

研究的目的:

开发一种新的单电极,接触分离的 triboelectric 纳米发电机 (CS-TENG) 用于语音信号的获取.
将CS-TENG集成到一个面具中,用于不引人注目的数据收集.
通过先进的信号处理来实现准确的扬声器内容和身份识别.

主要方法:

制造一个稳定的高频CS-TENG.
将CS-TENG集成到面具上,以捕捉语音期间的空气流动振动.
应用短时间里叶变换 (STFT),Mel频率塞普斯特拉系数 (MFCC) 和深度学习用于信号分析.
使用处理的语音数据来识别演讲者内容和身份.

主要成果:

CS-TENG显示了高频传感和长期稳定性.
通过空气流振动成功捕获了语音信号.
词汇识别准确度超过了92%.
发言人身份识别准确度超过了90%.

结论:

面具集成的CS-TENG系统可在安静的环境中实现安全和高效的不引人注目的通信.
这项技术在智能家居,虚拟助理和敏感环境中具有潜在的应用.
该系统为谨慎的人机交互提供了一种新的方法.

关键词:

人与计算机的互动.沉默的沟通是一种无声的沟通.语音识别语音识别语言识别 triboelectric纳米发电机的使用情况振动传感器振动传感器

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