当前位置: X-MOL 学术Nano Energy › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Anti-interference self-powered acoustic fabric for complex acoustic environments
Nano Energy ( IF 17.6 ) Pub Date : 2023-05-16 , DOI: 10.1016/j.nanoen.2023.108534
Jizhong Zhao , Yuan Yao , Wentao Lei , Li Zhao , Andeng Liu , Meidan Ye , Jianyang Wu , Shihui Guo , Wenxi Guo

Traditional airborne microphones are at risk of failure due to their dependence on airborne media in complex acoustic environments (CAEs). Here, we report an anti-interference self-powered acoustic fabric (ASAF) that can shield the interfering factors in the process of sound production and propagation to serve as a precise and wearable sound receiver. The use of the soft and safe woven structure polyvinylidene fluoride (PVDF) as a vibration-sensitive layer enables the ASAF to record human speech at wide vibration frequencies (0–5000 Hz). A speech recognition system is established which can recognize 25 words related to extreme weather conditions, with more than 95.8% accuracy. This speech recognition is carried out in CAEs such as wearing masks, silent communication, windstorms, and rainstorms, with corresponding losses of accuracy less than 1.6%, 6.7%, 6.3%, and 5.8%, respectively. The ASAF is expected to facilitate outdoor rescuers, journalists, students, and other professionals working in CAEs.



中文翻译:

用于复杂声学环境的抗干扰自供电声学织物

传统机载麦克风由于在复杂声学环境 (CAE) 中依赖机载介质而存在故障风险。在这里,我们报告了一种抗干扰自供电声学织物(ASAF),它可以屏蔽声音产生和传播过程中的干扰因素,作为一种精确的可穿戴声音接收器。使用柔软安全的编织结构聚偏二氟乙烯 (PVDF) 作为振动敏感层,使 ASAF 能够在宽振动频率 (0–5000 Hz) 下记录人类语音。建立了语音识别系统,可识别25个与极端天气情况相关的词,准确率超过95.8%。这种语音识别在戴口罩、无声交流、暴风雨等CAE中进行,相应的准确率损失小于1.6%,分别为 6.7%、6.3% 和 5.8%。ASAF 有望为户外救援人员、记者、学生和其他在 CAE 工作的专业人员提供便利。

更新日期:2023-05-16
down
wechat
bug