Wearable silent speech systems hold significant potential for restoring communication in patients with speech impairments. However, seamless, coherent speech remains elusive, and clinical efficacy is still unproven. Here, we present an AI-driven intelligent throat (IT) system that integrates throat muscle vibrations and carotid pulse signal sensors with large language model (LLM) processing to enable fluent, emotionally expressive communication. The system utilizes ultrasensitive textile strain sensors to capture high-quality signals from the neck area and supports token-level processing for real-time, continuous speech decoding, enabling seamless, delay-free communication. In tests with five stroke patients with dysarthria, IT's LLM agents intelligently corrected token errors and enriched sentence-level emotional and logical coherence, achieving low error rates (4.2% word error rate, 2.9% sentence error rate) and a 55% increase in user satisfaction. This work establishes a portable, intuitive communication platform for patients with dysarthria with the potential to be applied broadly across different neurological conditions and in multi-language support systems.

本研究解决了中风患者语言障碍的交流需求，提出了一种结合喉部肌肉振动和颈动脉脉搏信号的AI驱动智能喉咙系统，实现流畅且具有情感表现的交流。测试结果表明，该系统在中风患者中表现出较低的误差率和显著提高的用户满意度，显示出在多种神经疾病和多语言支持系统中的广泛应用潜力。

可穿戴智能喉咙为中风患者提供自然语言交流