Speaking without vocal folds using a machine-learning-assisted | ResearchBunny

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Abstract

This paper introduces a self-powered wearable sensing-actuation system for assisted speaking without vocal folds. The system, weighing 7.2 g, uses soft magnetoelasticity to capture laryngeal muscle movements, converting them into electrical signals with 94.68% accuracy via machine learning. These signals are then used to produce voice signals, bypassing vocal fold vibration. This technology aims to improve the quality of life for patients with vocal fold dysfunction.

Publisher

Nature Communications

Published On

Mar 12, 2024

Authors

Ziyuan Che, Xiao Wan, Jing Xu, Chrystal Duan, Tianqi Zheng, Jun Chen

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