In summary
- A portable device was developed that allowed patients with dysarthria to recover natural and expressive communication.
- The system processed emotional and silent speech signals in real time using advanced language models and sensors.
- Researchers tested the device, achieving high accuracy and significantly improving user satisfaction.
A new wearable device has been developed to allow patients with dysarthria – a motor speech disorder – to regain natural, fluent communication.
The “intelligent throat” system, created by an international team of researchers, combines advanced sensors and artificial intelligence (AI) to process silent speech and emotional signals in real time.
The system integrates textile strain sensors, which detect throat muscle vibrations, and carotid pulse signal monitors, along with large language models for speech processing.
Unlike existing technologies, the device translates silent speech into coherent sentences without delay, incorporating emotional and contextual nuances.
The system tested on five patients with dysarthria, achieved a word error rate of 4.2% and a sentence error rate of 2.9%, significantly improving existing silent speech systems.
Additionally, user satisfaction increased by 55%, highlighting its ability to provide personalized and expressive communication.
“The system generates personalized, contextually appropriate sentences that accurately reflect patients’ intended meaning,” notes a research paper presented Wednesday.
The design of the wearable device features an integrated “choker” with graphene-based strain sensors, offering high sensitivity and comfort for daily use.
A built-in wireless module ensures continuous data transmission with minimal power consumption, allowing operation throughout the day.
LLM agents embedded in the system analyze speech tokens and emotional cues, refining and expanding sentences to match the user’s intended meaning.
The personalized approach allows for dynamic expression in real time, bridging the gap between patient communication needs and technological capabilities, according to the researchers.
Researchers also envision broader applications, including support for other neurological conditions such as ALS and Parkinson’s, with the potential for multilingual adaptations.
The team is now focusing on miniaturizing the device and integrating it into edge computing frameworks to improve its usability, they wrote.
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