Ti3C2Tx复合气凝使压力传感器能够通过深度学习的帮助进行方言语音识别
Yanan Xiao1, He Li1, Tianyi Gu1
1State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, 130012, People's Republic of China.
Nano-micro letters
|December 31, 2024
概括
这项研究引入了一种超轻型气凝压力传感器,用于无声语音识别. 可穿戴设备准确地检测非标准语言和方言,增强人机通信.
科学领域:
- 材料科学 材料科学 材料科学
- 生物医学工程 生物医学工程
- 信号处理 信号处理
背景情况:
- 可穿戴式压力传感器为声音检测提供了潜力,但与非标准语言扎.
- 现有的语音助理缺乏对不同语言背景的包容性.
研究的目的:
- 开发一个具有包容性的可穿戴式压力传感器,用于识别非标准语言.
- 推进无声语音识别,以改善人机交互.
主要方法:
- 制造一个超轻的Ti3C2Tx MXene/chitosan/polyvinylidene二化物复合气凝.
- 描述气凝的压力传感能力 (检测范围,响应/恢复时间,歇斯底里).
- 利用卷积神经网络从传感器数据进行语音和方言识别.
主要成果:
- 气凝传感器显示了广泛的检测范围 (6.25 Pa1200 kPa),反应快速,歇斯底里低.
- 精确识别六个方言 (96.2%准确率) 和七个单词 (96.6%准确率) 已实现.
- 传感器有效捕获喉肌肉振动,用于无干扰的语音检测.
结论:
- 开发的气凝压力传感器显著提升了无声语音识别能力.
- 这项技术通过支持非标准语言,提高了人机交互的包容性.
- 该传感器在生理信号监控应用中表现有前途.
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