Ultrathin Eardrum-Inspired Self-Powered Acoustic Sensor for Vocal Synchronization Recognition with the Assistance of Machine Learning

doi:10.1002/smll.202106960

	Ultrathin Eardrum-Inspired Self-Powered Acoustic Sensor for Vocal Synchronization Recognition with the Assistance of Machine Learning
	Jiang, Yang 1,2; Zhang, Yufei 1,2; Ning, Chuan 1,2; Ji, Qingqing 3; Peng, Xiao 1,2; Dong, Kai 1,2; Wang, Zhong Lin 1,2,4,5
	2022-04-01
发表期刊	SMALL
ISSN	1613-6810
卷号	18 期号:13 页码:9
摘要	With the rapid development of human-machine interfaces, artificial acoustic sensors play an important role in the hearing impaired. Here, an ultrathin eardrum-like triboelectric acoustic sensor (ETAS) is presented consisting of silver-coated nanofibers, whose thickness is only 40 mu m. The sensitivity and frequency response range of the ETAS are closely related to the geometric parameters. The ETAS endows a high sensitivity of 228.5 mV Pa-1 at 95 dB, and the ETAS has a broad frequency response ranging from 20 to 5000 Hz, which can be tuned by adjusting the thickness, size, or shape of the sensor. Cooperating with artificial intelligence (AI) algorithms, the ETAS can achieve real-time voice conversion with a high identification accuracy of 92.64%. Under good working property and the AI system, the ETAS simplifies signal processing and reduces the power consumption. This work presents a strategy for self-power auditory systems, which can greatly accelerate the miniaturization of self-powered systems used in wearable electronics, augmented reality, virtual reality, and control hubs for automation.
关键词	acoustic sensors machine learning self-powered sensors triboelectric nanogenerators voice recognition
DOI	10.1002/smll.202106960
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[22109012] ; Natural Science Foundation of Beijing Municipality[2212052] ; Fundamental Research Funds for the Central Universities[E1E46805]
WOS研究方向	Chemistry ; Science & Technology - Other Topics ; Materials Science ; Physics
WOS类目	Chemistry, Multidisciplinary ; Chemistry, Physical ; Nanoscience & Nanotechnology ; Materials Science, Multidisciplinary ; Physics, Applied ; Physics, Condensed Matter
WOS记录号	WOS:000751371900001
出版者	WILEY-V C H VERLAG GMBH
引用统计	被引频次：60[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/18867
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Dong, Kai; Wang, Zhong Lin
作者单位	1.Chinese Acad Sci, Beijing Inst Nanoenergy & Nanosyst, Beijing 101400, Peoples R China 2.Univ Chinese Acad Sci, Sch Nanosci & Technol, Beijing 100049, Peoples R China 3.Univ Chinese Acad Sci, Chinese Acad Sci, Inst Comp Technol, Beijing 100049, Peoples R China 4.CUSTech Inst Technol, Wenzhou 325024, Zhejiang, Peoples R China 5.Georgia Inst Technol, Sch Mat Sci & Engn, Atlanta, GA 30332 USA
推荐引用方式 GB/T 7714	Jiang, Yang,Zhang, Yufei,Ning, Chuan,et al. Ultrathin Eardrum-Inspired Self-Powered Acoustic Sensor for Vocal Synchronization Recognition with the Assistance of Machine Learning[J]. SMALL,2022,18(13):9.
APA	Jiang, Yang.,Zhang, Yufei.,Ning, Chuan.,Ji, Qingqing.,Peng, Xiao.,...&Wang, Zhong Lin.(2022).Ultrathin Eardrum-Inspired Self-Powered Acoustic Sensor for Vocal Synchronization Recognition with the Assistance of Machine Learning.SMALL,18(13),9.
MLA	Jiang, Yang,et al."Ultrathin Eardrum-Inspired Self-Powered Acoustic Sensor for Vocal Synchronization Recognition with the Assistance of Machine Learning".SMALL 18.13(2022):9.