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From Thought to Text: AI Converts Silent Speech into Written Words

 

Summary: A novel artificial intelligence system, the semantic decoder, can translate brain activity into continuous text. The system could revolutionize communication for people unable to speak due to conditions like stroke.

This non-invasive approach uses fMRI scanner data, turning thoughts into text without requiring any surgical implants. While not perfect, this AI system successfully captures the essence of a person’s thoughts half of the time.

Key Facts:

  1. The semantic decoder AI was developed by researchers at The University of Texas at Austin.
  2. It works based on a transformer model similar to the ones that power Open AI’s ChatGPT and Google’s Bard.
  3. The system has potential for use with more portable brain-imaging systems, like functional near-infrared spectroscopy (fNIRS).

Source: UT Austin

A new artificial intelligence system called a semantic decoder can translate a person’s brain activity — while listening to a story or silently imagining telling a story — into a continuous stream of text.

The system developed by researchers at The University of Texas at Austin might help people who are mentally conscious yet unable to physically speak, such as those debilitated by strokes, to communicate intelligibly again.

The study, published in the journal Nature Neuroscience, was led by Jerry Tang, a doctoral student in computer science, and Alex Huth, an assistant professor of neuroscience and computer science at UT Austin.

Credit: Neuroscience News

The work relies in part on a transformer model, similar to the ones that power Open AI’s ChatGPT and Google’s Bard.

 

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