中文摘要：

为健全信号获得和识别的一个便携、高精确的传感器从编织的特殊设计的 graphene 的薄电影被制作织物(GWF ) 。在被拉长之上，随机的裂缝的高密度出现在网络，它减少当前的小径，从而增加电阻。因此，这部电影能对人的喉咙作为一个紧张传感器起作用以便测量通过肌肉运动，一个声音是否被生产的讲话。超离频敏感允许由提取声波的签名特征的快速、低频率的讲话采样的实现。在这研究， 26 封英语信，典型汉字和音调的代表性的信号，甚至短语和句子被测试，揭示在电阻的明显、典型的变化。而且， graphene 传感器的电阻变化与预告录下的声音完美地反应了。由把人工智能与数字信号处理相结合，我们期望以后，这个 graphene 传感器将能成功地达成复杂声学的系统和听觉的数据的大数量。

英文摘要：

A wearable and high-precision sensor for sound signal acquisition and recognition was fabricated from thin films of specially designed graphene woven fabrics （GWFs）. Upon being stretched, a high density of random cracks appears in the network, which decreases the current pathways, thereby increasing the resistance. Therefore, the film could act as a strain sensor on the human throat in order to measure one＇s speech through muscle movement, regardless of whether or not a sound is produced. The ultra-high sensitivity allows for the realization of rapid and low-frequency speech sampling by extracting the signature characteristics of sound waves. In this study, representative signals of 26 English letters, typical Chinese characters and tones, and even phrases and sentences were tested, revealing obvious and characteristic changes in resistance. Furthermore, resistance changes of the graphene sensor responded perfectly with pre-recorded sounds. By combining artificial intelligence with digital signal processing, we expect that, in the future, this graphene sensor will be able to successfully negotiate complex acoustic systems and large quantities of audio data.