Brain-Computer Interfaces Can Now Decode Speech at 78 WPM, But Challenges Remain

Researchers have developed brain-computer interface pipelines capable of decoding attempted speech from motor cortex signals, with leading systems achieving between 32 and 78 words per minute depending on electrode type and vocabulary size. The Willett et al. (Nature 2023) study used 256 intracortical electrodes and a recurrent neural network with language model rescoring to reach 62 words per minute, while Card et al. (NEJM 2024) later sustained 97.5% accuracy over 8.4 months. A key technical challenge is electrode drift, which causes signal changes day to day and requires decoders to recalibrate regularly, often through per-day input layers. Non-invasive approaches like MEG and EEG perform significantly worse, with character error rates of 32% and 67% respectively, while Meta's surface EMG-based Neural Band shipped in late September 2025 offering a calibration-free alternative at around 21 words per minute. The output side of the equation — delivering AI-generated visuals directly into human perception via the visual cortex — remains an open and largely unsolved research problem.