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TENG-Based Self-Powered Silent Speech Recognition Interface: from Assistive Communication to Immersive AR/VR Interaction

Authors: Shuai Lin; Yanmin Guo; Xiangyao Zeng; Xiongtu Zhou; Yongai Zhang; Chengda Li; Chaoxing Wu

DOI: 10.1007/s40820-025-01982-zStatus: Verified Translated Edition

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Key Findings in This Report

• A porous pyramid-structured triboelectric nanogenerator sensor is designed for self-powered silent speech signal acquisition. • A hybrid neural network combining CNN and LSTM accurately decodes silent speech signals with 95.83% accuracy across 30 word categories. • Silent speech commands enable real-time, contactless control of smartphones and immersive AR/VR interaction. • The system offers a novel human-machine interaction approach with high sensitivity in low-force pressure detection.