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Brain–machine-interface device translates internal speech into text - Nature.com

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For patients affected by speech disorders, brain–machine-interface (BMI) devices could restore their ability to verbally communicate. In this work, we captured neural activity associated with internal speech — words said within the mind with no associated movement or audio output — and translated these cortical signals into text in real time.

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Fig. 1: Internal and vocalized speech are significantly decodable both offline and online.

References

  1. Makin, J. G., Moses, D. A. & Chang, E. F. Machine translation of cortical activity to text with an encoder–decoder framework. Nat. Neurosci. 23, 575–582 (2020). An article that presents high-accuracy vocalized speech decoding into text using electrocorticogram data.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Moses, D. A. et al. Neuroprosthesis for decoding speech in a paralyzed person with anarthria. N. Engl. J. Med. 385, 217–227 (2021). An article that presents high-accuracy attempted speech decoding into text using electrocorticogram data.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Willett, F. R. et al. A high-performance speech neuroprosthesis. Nature 620, 1031–1036 (2023). An article that presents high-accuracy attempted and mimed speech decoding into text using multielectrode arrays.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Metzger, S. L. et al. A high-performance neuroprosthesis for speech decoding and avatar control. Nature 620, 1037–1046 (2023). An article that presents high-accuracy attempted and mimed speech decoding into text, audio and avatar movement using electrocorticogram data.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Wandelt, S. K. et al. Decoding grasp and speech signals from the cortical grasp circuit in a tetraplegic human. Neuron 110, 1777–1787 (2022). An article that presents grasp and vocalized speech decoding from the SMG.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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This is a summary of: Wandelt, S. K. et al. Representation of internal speech by single neurons in human supramarginal gyrus. Nat. Hum. Behav. https://doi.org/10.1038/s41562-024-01867-y (2024).

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Brain–machine-interface device translates internal speech into text. Nat Hum Behav (2024). https://ift.tt/PzjMd3T

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