{"id":243560,"date":"2025-04-16T10:00:01","date_gmt":"2025-04-16T10:00:01","guid":{"rendered":"https:\/\/peoplebugs.com\/top-stories\/ai-system-restores-speech-for-paralyzed-patients-using-own-voice\/"},"modified":"2025-04-16T10:30:31","modified_gmt":"2025-04-16T10:30:31","slug":"ai-system-restores-speech-for-paralyzed-patients-using-own-voice","status":"publish","type":"post","link":"https:\/\/peoplebugs.com\/top-stories\/ai-system-restores-speech-for-paralyzed-patients-using-own-voice\/","title":{"rendered":"AI system restores speech for paralyzed patients using own voice"},"content":{"rendered":"


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Researchers in California<\/a> have achieved a significant breakthrough with an AI-powered system that restores natural speech to paralyzed individuals in real time, using their own voices, specifically demonstrated in a clinical trial participant who is severely paralyzed and cannot speak.\u00a0<\/p>\n

This innovative technology, developed by teams at UC Berkeley and UC San Francisco, combines brain-computer interfaces (BCI) with advanced artificial intelligence<\/a> to decode neural activity into audible speech.\u00a0<\/p>\n

Compared to other recent attempts to create speech from brain signals, this new system is a major advancement.<\/p>\n

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AI-powered system<\/span> (Kaylo Littlejohn, Cheol Jun Cho, et al. Nature Neuroscience 2025)<\/span><\/p>\n<\/div>\n<\/div>\n<\/div>\n

How it works<\/strong><\/h2>\n

The system uses devices such as high-density electrode arrays that record neural activity directly from the brain’s surface. It also works with microelectrodes that penetrate the brain\u2019s surface and non-invasive surface electromyography sensors placed on the face to measure muscle activity. These devices tap into the brain to measure neural activity, which the AI then learns to transform into the sounds of the patient’s voice.\u00a0<\/p>\n

The neuroprosthesis samples neural data from the brain’s motor cortex, the area controlling speech production, and AI decodes that data into speech. According to study co-lead author Cheol Jun Cho, the neuroprosthesis intercepts signals where the thought is translated into articulation and, in the middle of that, motor control.<\/p>\n

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AI-powered system<\/span> (Kaylo Littlejohn, Cheol Jun Cho, et al. Nature Neuroscience 2025)<\/span><\/p>\n<\/div>\n<\/div>\n<\/div>\n

AI ENABLES PARALYZED MAN TO CONTROL ROBOTIC ARM WITH BRAIN SIGNALS<\/u><\/strong><\/a><\/p>\n

Key advancements<\/strong><\/h2>\n