Ultrathin Eardrum-Inspired Self-Powered Acoustic Sensor for Vocal Synchronization Recognition with the Assistance of Machine Learning
文献类型：期刊论文
| 作者 | Jiang, Yang1,2; Zhang, Yufei1,2; Ning, Chuan1,2; Ji, Qingqing3; Peng, Xiao1,2; Dong, Kai1,2; Wang, Zhong Lin1,2,4,5 |
| 刊名 | SMALL
 |
| 出版日期 | 2022-04-01 |
| 卷号 | 18期号:13页码:9 |
| ISSN号 | 1613-6810 |
| 关键词 | acoustic sensors machine learning self-powered sensors triboelectric nanogenerators voice recognition |
| DOI | 10.1002/smll.202106960 |
| 英文摘要 | 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. |
| 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 |
| 语种 | 英语 |
| 出版者 | WILEY-V C H VERLAG GMBH |
| WOS记录号 | WOS:000751371900001 |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/18866]  |
| 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. |
入库方式： OAI收割
来源：计算技术研究所
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