Speech recognition using intelligent piezoresistive sensor based on polystyrene sphere microstructures

Liu, Y., Li, H., Liang, X., Deng, H., Zhang, X., Heidari, H. , Ghannam, R. and Zhang, X. (2023) Speech recognition using intelligent piezoresistive sensor based on polystyrene sphere microstructures. Advanced Intelligent Systems, 5(7), 2200427. (doi: 10.1002/aisy.202200427)

Abstract

Rapid advances in wearable sensing technology have demonstrated unprecedented opportunities for artificial intelligence. In comparison with the traditional hand-held electrolarynx, a wearable and intelligent artificial throat with sound-sensing ability is a more comfortable and versatile method to assist disabled people with communication. Herein, a piezoresistive sensor with a novel configuration is demonstrated, which consists of polystyrene (PS) spheres as microstructures sandwiched between silver nanowires and reduced graphene oxide layers. In fact, changes in the device's conducting patterns are obtained by spay-coating the various weight ratios and sizes of the PS microspheres, which is a fast and convenient way to establish microstructures for improving sensitivity. The wearable artificial throat device also exhibits high sensitivity, fast response time, and ultralow intensity level detection. Moreover, the device's excellent mechanical–electrical performance allows it to detect subtle throat vibrations that can be converted into controllable sounds. In this case, an intelligent artificial throat is achieved by combining a deep learning algorithm with a highly flexible piezoresistive sensor to successfully recognize five different words (help, sick, patient, doctor, and COVID) with an accuracy exceeding 96%. Herein, new opportunities in voice control as well as other human-machine interface applications are opened.

• Item Type: Articles
• Additional Information: This work was financially supported by the National Natural Science Foundation of China (no. 62074029, no. 61804023, no. 61971108), the Key R&D Program of Sichuan Province (no. 2022JDTD0020 and no. 2020ZHCG0038), the Sichuan Science and Technology Program (no. 2019YJ0198 and no. 2020YJ0015), and the Fundamental Research Funds for the Central Universities (no. ZYGX2019Z002).
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Liang, Xiangpeng and Ghannam, Professor Rami and Heidari, Professor Hadi and Liu, Miss Yuchi
• Authors: Liu, Y., Li, H., Liang, X., Deng, H., Zhang, X., Heidari, H., Ghannam, R., and Zhang, X.
• College/School: College of Science and Engineering > School of Engineering; College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
• Journal Name: Advanced Intelligent Systems
• Publisher: Wiley
• ISSN: 2640-4567
• ISSN (Online): 2640-4567
• Published Online: 06 April 2023
• Copyright Holders: Copyright © 2023 The Authors
• First Published: First published in Advanced Intelligent Systems 5(7):2200427
• Publisher Policy: Reproduced under a Creative Commons License