用于无声交流和语音识别的可穿戴式光子人工喉

IF 8.2 2区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY
Wenbo Li, Rui Min, Di Zheng, Yukun Long, Kun Xiao, Zhuo Wang, Mo Guo, Qingming Chen, Lanfang Liu, Xiaoli Li, Zhaohui Li
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引用次数: 0

摘要

最近,倡导残疾人发声,特别是通过可穿戴的人工咽喉,引起了人们的极大关注。这种装置需要具有可拉伸性、高灵敏度和良好的皮肤顺应性的传感器。本研究开发了一种智能光子人工喉。它的特点是将三明治结构的光纤传感器封装在龙皮20中,龙皮20具有与人体组织相似的弹性模量,并集成了增强灵敏度的环和织物,以增强耐磨性。它具有超快的响应速度(响应时间为10 ms,恢复时间为32 ms)和高灵敏度(1.92 μW/mN),可检测喉部振动和肌肉收缩,准确识别普通话声调、元音、英语单词和句子,实现准确的双语检测。当安装在扬声器上时,它还能区分动物的声音(马的嘶鸣和布谷鸟的叫声)和流行歌曲。此外,人工咽喉可以准确地检测到头部和颈部的细微动作,并将点头动作与莫尔斯电码相结合,成功地实现了个体之间的无声交流。与先进的人工智能(AI)算法相结合,它可以识别音调(97.50%)、元音字母(97.00%)、常用语(98.00%)和句子(96.52%),为生物医学应用、语言教育、语音识别、运动监测等领域开辟了前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Wearable Photonic Artificial Throat for Silent Communication and Speech Recognition

Wearable Photonic Artificial Throat for Silent Communication and Speech Recognition
Advocating for the voices of the disabled, particularly through wearable artificial throats, has garnered significant attention recently. Such devices necessitate sensors with stretchability, high sensitivity, and excellent skin conformability. In this study, an intelligent photonic artificial throat has been developed. It features a sandwich-structured optical fiber sensor encapsulated in Dragon Skin 20, which has an elastic modulus similar to human tissue and is integrated with sensitivity-enhancing rings and fabric for enhanced wearability. With ultrafast response (response time: 10 ms, recovery time: 32 ms) and high sensitivity (1.92 μW/mN), it detects throat area vibrations and muscle contractions, accurately identifying tones in Mandarin, vowels, words, and sentences in English, achieving accurate bilingual detection. It also distinguishes animal sounds (horse neighing and cuckoo’s call) and pop songs when mounted on speakers. Furthermore, the artificial throat can accurately detect subtle movements of the head and neck, and by combining nodding actions with the MORSE code, silent communication between individuals has been successfully achieved. Integrated with an advanced artificial intelligence (AI) algorithm, it recognizes tones (97.50%), vowel letters (97.00%), common words (98.00%) and sentences (96.52%), opening prospects for biomedical applications, language education, speech recognition, motion monitoring, and more.
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来源期刊
ACS Applied Materials & Interfaces
ACS Applied Materials & Interfaces 工程技术-材料科学:综合
CiteScore
16.00
自引率
6.30%
发文量
4978
审稿时长
1.8 months
期刊介绍: ACS Applied Materials & Interfaces is a leading interdisciplinary journal that brings together chemists, engineers, physicists, and biologists to explore the development and utilization of newly-discovered materials and interfacial processes for specific applications. Our journal has experienced remarkable growth since its establishment in 2009, both in terms of the number of articles published and the impact of the research showcased. We are proud to foster a truly global community, with the majority of published articles originating from outside the United States, reflecting the rapid growth of applied research worldwide.
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