Scientists develop noninvasive AI system to translate brain activity into text

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Scientists at the University of Texas at Austin have developed a non-invasive AI system called a semantic decoder that can translate a person’s brain activity into a stream of text. The system has the potential to aid patients who have lost their ability to communicate due to degenerative diseases, paralysis or a stroke.

The study involved participants listening to several hours of podcasts while in an fMRI scanner that measures brain activity. Once trained, the AI system can generate a stream of text when the participant listens to or imagines telling a new story. The resultant text captures general thoughts or ideas rather than an exact transcript.

The trained system was able to produce text that matched the intended meaning of the participant’s words about half of the time. For instance, when a participant heard the words “I don’t have my driver’s license yet,” the thoughts were translated to “She has not even started to learn to drive yet.”

The researchers noted that this is a significant improvement over previous methods that typically only translate single words or short sentences. The AI system was also able to accurately describe “certain events” from videos watched by participants without audio.

Currently, the system requires an fMRI scanner, limiting its use to laboratory settings. However, the researchers believe that it could eventually be used via more portable brain-imaging systems.

The technology has the potential to aid people who have lost their ability to communicate due to degenerative diseases or other neurological conditions. The researchers have filed a PCT patent application for the technology.

“This is a real leap forward,” said Alexander Huth, one of the study’s leaders. “We’re getting the model to decode continuous language for extended periods of time with complicated ideas. For a non-invasive method, this is a real leap forward compared to what’s been done before, which is typically single words or short sentences.”

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Scientists develop noninvasive AI system to translate brain activity into text

Scientists at the University of Texas at Austin have developed a non-invasive AI system called a semantic decoder that can translate a person’s brain activity into a stream of text. The system has the potential to aid patients who have lost their ability to communicate due to degenerative diseases, paralysis or a stroke.

The study involved participants listening to several hours of podcasts while in an fMRI scanner that measures brain activity. Once trained, the AI system can generate a stream of text when the participant listens to or imagines telling a new story. The resultant text captures general thoughts or ideas rather than an exact transcript.

The trained system was able to produce text that matched the intended meaning of the participant’s words about half of the time. For instance, when a participant heard the words “I don’t have my driver’s license yet,” the thoughts were translated to “She has not even started to learn to drive yet.”

The researchers noted that this is a significant improvement over previous methods that typically only translate single words or short sentences. The AI system was also able to accurately describe “certain events” from videos watched by participants without audio.

Currently, the system requires an fMRI scanner, limiting its use to laboratory settings. However, the researchers believe that it could eventually be used via more portable brain-imaging systems.

The technology has the potential to aid people who have lost their ability to communicate due to degenerative diseases or other neurological conditions. The researchers have filed a PCT patent application for the technology.

“This is a real leap forward,” said Alexander Huth, one of the study’s leaders. “We’re getting the model to decode continuous language for extended periods of time with complicated ideas. For a non-invasive method, this is a real leap forward compared to what’s been done before, which is typically single words or short sentences.”

Disclaimer

We strive to uphold the highest ethical standards in all of our reporting and coverage. We StartupNews.fyi want to be transparent with our readers about any potential conflicts of interest that may arise in our work. It’s possible that some of the investors we feature may have connections to other businesses, including competitors or companies we write about. However, we want to assure our readers that this will not have any impact on the integrity or impartiality of our reporting. We are committed to delivering accurate, unbiased news and information to our audience, and we will continue to uphold our ethics and principles in all of our work. Thank you for your trust and support.

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