AI-Powered Brain Implant Restores Real-Time Speech for Paralyzed Stroke Survivor

Researchers at UC Berkeley and UCSF achieve a breakthrough in brain-computer interfaces, enabling a woman to speak in her own voice after 18 years of silence.

The brain-computer interface (BCI) system uses AI to decode neural signals from the motor cortex into audible speech with less than one second of delay.
The technology was successfully tested on Ann Johnson, a stroke survivor who lost her ability to speak 18 years ago, allowing her to communicate in her pre-injury voice.
The system employs a high-density electrocorticography (ECoG) array to collect neural data and a personalized AI model trained on recordings of Ann's voice to produce natural-sounding speech.
Researchers demonstrated the system's ability to generalize beyond its training data, accurately synthesizing words outside its initial vocabulary.
Future advancements aim to enhance expressivity by incorporating tone, pitch, and loudness, with broader applications being explored, including non-invasive methods.