A woman who hasn’t uttered a word for after a paralyzing stroke has regained the ability to through artificial intelligence.

The groundbreaking procedure uses an array of 253 electrodes implanted in the brain of Ann Johnson, 48, which are linked to a bank of computers through a small port connection affixed to her head.

The electrodes, which cover the area of the brain where speech is processed, intercept her brain signals and send them to the computers, which also display Johnson’s brown-haired avatar on a computer screen.

The on-screen avatar — which Johnson chose herself — is then able to “” what she is thinking, using a copy of her voice recorded ago during a 15-minute toast she gave at her wedding.

The avatar also blinks its eyes and uses facial expressions such as smiles, pursed lips and raised eyebrows, making it seem more lifelike.

“We’re just trying to restore who people are,” Dr. Edward Chang, the chairman of neurological surgery at the University of California, San Francisco, told the New York Times.

Johnson — a high-school math teacher who was also active as a volleyball and basketball coach in Saskatchewan — was married for two and had two children when a stroke rendered her .

Ann Johnson is now able to “talk,” through a digital avatar, for the first time in since a stroke rendered her .Noah Berger / SWNS

“Not being able to hug and kiss my children hurt so bad, but it was my reality,” Johnson said. “The real nail in the coffin was being told I couldn’t have more children.”

After of rehabilitation, she gradually regained some movement and facial expression, but Johnson remained to speak and had to be tube-fed until swallowing therapy allowed her to eat finely chopped or soft foods.

“My daughter and I love cupcakes,” Johnson said.

The team from the University of California, San Francisco and nearby colleagues at the University of California, Berkeley, said it’s the first time either speech or facial expressions have been synthesized from brain signals.

To train the AI system, Johnson had to silently “repeat” different phrases from a 1,024-word vocabulary over and over until the computer recognized the brain activity pattern associated with each sound.

Instead of whole words, the AI program was taught to recognize phonemes, the units of speech that form spoken words. “Hello,” for example, contains four phonemes: “HH,” “AH,” “L” and “OW.”

By recognizing 39 phonemes, the AI program can decode Johnson’s brain signals into complete words at a rate of about 80 words a minute — roughly half the rate of normal person-to-person dialogue.

Johnson worked with UCSF researchers to train an AI system to recognize her brain signals and convert them into speech.Noah Berger / SWNS

Sean Metzger, who developed the decoder in the joint Bioengineering Program at UC Berkeley and UCSF, told South West News Service, “The accuracy, speed and vocabulary are crucial.

“It’s what gives a user the potential, in time, to communicate almost as fast as we do, and to have much more naturalistic and normal conversations.”

The team is now working on a wireless version, which means the user won’t have to be physically connected to the computers with wires or cables.

Chang has worked on the brain-computer interface for more than a decade and hopes the team’s innovation will lead to a system that enables speech from brain signals in the near future.

“Our goal is to restore a full, embodied way of communicating, which is really the most natural way for us to talk with others,” Chang told SWNS.

“These advancements bring us much closer to making this a real solution for patients,” Chang added.

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