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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References
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.
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.
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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://doi.org/10.1038/s41562-024-01869-w
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DOI: https://doi.org/10.1038/s41562-024-01869-w
