A brain implant has restored the conversation in a violent paralyzed woman, which is the progress of breakthrough in providing communication for people who lost their ability to speak.
Implant is detailed in a study published in the magazine. NATURE NERVELATION On Monday, it solves a long -standing delay difficulty in using a prosthesis for a speech.
Researchers, including the University of California Berkeley, developed an artificial intelligence system to synthesize and convey brain signals to “real time” to the “real time”.
Gopala Anumanchipalli, author of the study, brings the same fast speech code -solving capacity of devices such as Alexa and Siri to neuroprostheses.
Cheol Jun Cho, another writer, said, “So, after deciding what to say, what words we use and how to move our vocal aspect after deciding how to move our muscles.
The researchers collected data from Ann from their subjects to train AI algorithms. “Hey, how are you?” And he quietly tried to talk about this sentence.
Another author of the study Kaylo Littlejohn said, “This gave us a match between the fragmented windows of the neural activity and the target sentence he tried to say without the need to voice at any point,” he said.
Scientists later used AI to fill the missing details in Ann’s brain signals.
“We used a pre-trained text-speech model to create a sound and simulate a target. And we also used Ann’s pre-injury, so it looks like him when we solved the output, Mr. Cheol said.
In the previous studies on the speech prosthesis, the researchers experienced a eight -second delay for a single sentence and a long delay to solve the conversation.
In a new approach, they say that a can be produced in a real time while “trying to talk to the subject”.
Anumanchipalli, “We can see according to this signal of intention, we make the first sound in 1 second. And the device can constantly solve the conversation, so the mother can continue to speak uninterrupted,” he said.
Scientists also tested the ability to synthesize words that are not part of the vocabulary, the educational data set of the AI model. “We found that our model did it well, which shows that it really learns sound or sound building blocks,” he added.
“This concept of evidence of the concept is quite a breakthrough. We are optimistic about that we can make progress at all levels now, C Cheol added.
