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Silent Speech Decoding for Dysarthria Using sEMG

CWSF · 2026 Health & Wellness

Ayomipo Oduntan · Intermediate Division · Grades 9–10

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Overview

Verbal communication is a fundamental aspect of our daily lives, yet millions of people struggle to speak clearly due to speech disorders. These speech disorders include Dysarthria, a speech disorder caused by weakness or poor coordination of the muscles used for speaking, which results in slurred, slow, or unclear speech. This project investigates how facial muscle signals measured using surface electromyography (sEMG), a technique that measures electrical activity produced by muscles, can be used to detect intended speech from Dysarthric patients. By placing sEMG sensors on the key speech muscles (masseters and submental region), the device detects the muscle signals associated with intended speech and uses machine learning models to identify and generate audible output.

Awards (1)

  • Selected for CWSF 2026

Competition history

  • CWSF 2026 Health & Wellness

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