Wearable intelligent throat enables natural speech in stroke patients with dysarthria

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.

@article{tang2025_2411.18266,
  title={ Wearable intelligent throat enables natural speech in stroke patients with dysarthria },
  author={ Chenyu Tang and Shuo Gao and Cong Li and Wentian Yi and Yuxuan Jin and Xiaoxue Zhai and Sixuan Lei and Hongbei Meng and Zibo Zhang and Muzi Xu and Shengbo Wang and Xuhang Chen and Chenxi Wang and Hongyun Yang and Ningli Wang and Wenyu Wang and Jin Cao and Xiaodong Feng and Peter Smielewski and Yu Pan and Wenhui Song and Martin Birchall and Luigi G. Occhipinti },
  journal={arXiv preprint arXiv:2411.18266},
  year={ 2025 }
}