Issue

Vol. 17 (2025)

Ti3C2Tx Composite Aerogels Enable Pressure Sensors for Dialect Speech Recognition Assisted by Deep Learning

https://doi.org/10.1007/s40820-024-01605-z
Yanan Xiao
State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun 130012, People’s Republic of China
He Li
State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun 130012, People’s Republic of China
Tianyi Gu
State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun 130012, People’s Republic of China
Xiaoteng Jia
State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun 130012, People’s Republic of China
Shixiang Sun
State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun 130012, People’s Republic of China
Yong Liu
State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun 130012, People’s Republic of China
Bin Wang
State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun 130012, People’s Republic of China
He Tian
School of Integrated Circuits, Tsinghua University, Beijing 100084, People’s Republic of China
Peng Sun
State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun 130012, People’s Republic of China
Fangmeng Liu
State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun 130012, People’s Republic of China
Geyu Lu
State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun 130012, People’s Republic of China

Corresponding Author: Fangmeng Liu

liufangmeng@jlu.edu.cn

Nano-Micro Letters, Vol. 17 (2025), Article Number: 101

Abstract

Wearable pressure sensors capable of adhering comfortably to the skin hold great promise in sound detection. However, current intelligent speech assistants based on pressure sensors can only recognize standard languages, which hampers effective communication for non-standard language people. Here, we prepare an ultralight Ti3C2Tx MXene/chitosan/polyvinylidene difluoride composite aerogel with a detection range of 6.25 Pa-1200 kPa, rapid response/recovery time, and low hysteresis (13.69%). The wearable aerogel pressure sensor can detect speech information through the throat muscle vibrations without any interference, allowing for accurate recognition of six dialects (96.2% accuracy) and seven different words (96.6% accuracy) with the assistance of convolutional neural networks. This work represents a significant step forward in silent speech recognition for human–machine interaction and physiological signal monitoring.


Highlights:
1 Emphasized the innovation in both the material design and methodology between the sensing performance and mechanical properties.
2 The composite aerogel pressure sensors exhibited low hysteresis (13.69%), wide detection range (6.25 Pa-1200 kPa), and cyclic stability to acquire stable and accurate pronunciation signals.
3 Over 6888 and 4158 pronunciation signals were collected by the pressure sensor and utilized for training the convolutional neural network model, allowing for accurate recognition of six dialects (96.2% accuracy) and seven words (96.6% accuracy).

Keywords

Pressure sensor Wearable sensor Ti3C2Tx composite aerogel Dialect speech recognition
Xiao, Yanan, He Li, Tianyi Gu, Xiaoteng Jia, Shixiang Sun, Yong Liu, Bin Wang, He Tian, Peng Sun, Fangmeng Liu, and Geyu Lu. 2024. “Ti3C2Tx Composite Aerogels Enable Pressure Sensors for Dialect Speech Recognition Assisted by Deep Learning”. Nano-Micro Letters 17 (December):101. https://doi.org/10.1007/s40820-024-01605-z.
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