Brain-Computer Interface Enables Internal Speech Translation for Tetraplegic Individuals

Researchers developed a brain-computer interface that translates internal speech into text in real-time, capturing neural activity associated with internal speech. The study demonstrated that people with tetraplegia can internally and vocally speak up to eight words using the BCI device.

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Aqsa Younas Rana
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Brain-Computer Interface Enables Internal Speech Translation for Tetraplegic Individuals

Brain-Computer Interface Enables Internal Speech Translation for Tetraplegic Individuals

In a groundbreaking study, researchers have developed a brain-computer interface (BCI) that can translate internal speech, or words thought but not spoken, into text in real-time. This breakthrough has the potential to restore verbal communication for individuals affected by speech disorders, such as tetraplegia.

Why this matters: This development has significant implications for the millions of people worldwide living with speech disorders, offering a potential solution to restore their ability to communicate effectively. Furthermore, this breakthrough could pave the way for advancements inbrain-machine interfaces and neural prosthetics, revolutionizing the field of assistive technology.

The BCI device captured neural activity associated with internal speech and translated these cortical signals into text in real-time. The study demonstrated that people with tetraplegia can internally and vocally speak up to eight words using the BCI device. Notably, the research showed strong shared neural representations between internal speech, vocalized speech, and written cues in the posterior parietal cortex.

Previous studies have focused on decoding vocalized speech or attempted speech into text using electrocorticogram data or multielectrode arrays. This study builds upon earlier research, including a 2020 study that presented high-accuracy vocalized speech

The development of this BCI device has the potential to revolutionize communication for individuals with speech disorders, enabling them to express themselves more effectively. The study's findings could also have broader implications for the development of brain-machine interfaces and neural prosthetics.

high-performance speech neuroprosthesis

The study was published in Nature Human Behaviour on May 13, 2024. The breakthrough in translating internal speech into text using a brain-computer interface marks a significant step forward in restoring communication for individuals with speech disorders. As research in this field continues to progress, it holds the promise of enhancing the quality of life for those affected by conditions such as tetraplegia.

Key Takeaways

  • Researchers develop brain-computer interface to translate internal speech into text in real-time.
  • Breakthrough has potential to restore verbal communication for individuals with speech disorders.
  • BCI device captures neural activity and translates into text, enabling internal speech up to 8 words.
  • Study shows strong neural representations between internal speech, vocalized speech, and written cues.
  • Development has implications for brain-machine interfaces, neural prosthetics, and assistive technology.