A stroke survivor speaks again with the help of an experimental brain-computer implant

AI and BCI Transform Thoughts to Speech in Near Real-Time

An AI-powered brain-computer interface (BCI) solution translates brain activity into synthesized speech at nearly real-time speed.

New AI Model Lets People Speak Using Only Their Thoughts

Researchers have developed a brain-to-voice interface that converts impulses into natural speech in real time — enabling restored communication for paralysis patients.

Breakthrough implant reads your thoughts and converts them to speech

A new thought-reading brain implant is giving people who can’t speak a chance to communicate again. Developed by researchers at UC Berkeley, this experimental technology can convert neural activity into spoken words with a delay of just a few seconds. It’s one of the closest breakthroughs yet toward real-time thought-to-voice communication. The system works by placing 253 electrodes on the surface of the brain, specifically targeting the motor c…

A high-performance speech neuroprosthesis

Speech brain–computer interfaces (BCIs) have the potential to restore rapid communication to people with paralysis by decoding neural activity evoked by attempted speech into text1,2 or sound3,4. Early demonstrations, although promising, have not yet achieved accuracies sufficiently high for communication of unconstrained sentences from a large vocabulary1–7. Here we demonstrate a speech-to-text BCI that records spiking activity from intracortic…

AI Tools Helped Restore Speech for a Woman With Paralysis: 'She Felt Embodied'

Scientists used a brain implant and generative AI to give a woman her voice back and help her talk in near real time.

New thought-to-speech brain device allows for ‘natural conversation’

Neuroscientists inched closer last week to developing a commercial device that can instantly translate brain activity into speech for people with severe paralysis. A team of researchers from University of California, Berkeley and University of California, San Francisco were able to solve a key problem for many brain-computer interfaces: lag. Their Nature Neuroscience study describes how the device shrunk the time between a person’s thoughts and …