Winner of Chen Institute and Science Prize Uses AI to Rebuild Speech from Brain Signals

By: Meagan Phelan

When Sergey Stavisky first started thinking about brain-computer interfaces (BCI) as an undergraduate at Brown University, he was motivated by three factors. “I liked building things,” he recalled, “and I wanted to do something medical. But I was also fascinated by the mind.”

That combination would lead Stavisky into a field that is now rapidly redefining what it means to lose, and potentially regain, a voice.

Today, Stavisky is an associate professor of neurological surgery at the University of California, Davis, and a leading figure in the development of AI-powered speech neuroprostheses. His work, recognized this year by the Chen Institute and Science Prize for Al Accelerated Research, sits at the intersection of neuroscience, clinical care and machine learning. But at its core is a simple goal: restoring the ability to speak to people who have lost it.

That goal becomes vivid in the story of one participant in his team’s research, a man living with amyotrophic lateral sclerosis (ALS) who could no longer speak intelligibly.

Through an implantable device and a suite of AI models trained on his brain activity that Stavisky and his team designed, the man is now able to generate fluent sentences — first as text, then as synthetic speech modeled on his own pre-ALS voice. In moments of daily use, he has produced millions of words.

Read more on the AAAS website.