Brain implant helps woman with paralysis speak with her own voice again

Researchers have developed a new method for intercepting neural signals from the brain of a person with paralysis and translating them into audible speech--all in near real-time. The result is a brain-computer interface (BCI) system similar to an advanced version of Google Translate, but instead of converting one language to another, it deciphers neural data and transforms it into spoken sentences. Recent advancements in machine learning have enabled researchers to train AI voice synthesizers using recordings of the individual's own voice, making the generated speech more natural and personalized. Patients with paralysis have already used BCI to improve physical motor control function by controlling computer mice and prosthetic limbs. This particular system addresses a more specific subsection of patients who have also lost their capacity to speak.