Data for: An accurate and rapidly calibrating speech neuroprosthesis

Brain-computer interfaces can enable communication for people with
paralysis by transforming cortical activity associated with attempted
speech into text on a computer screen. Communication with brain-computer
interfaces has been restricted by extensive training requirements and
limited accuracy. A 45-year-old man with amyotrophic lateral sclerosis
(ALS) with tetraparesis and severe dysarthria underwent surgical
implantation of four microelectrode arrays into his left ventral
precentral gyrus 5 years after the onset of the illness; these arrays
recorded neural activity from 256 intracortical electrodes. We report the
results of decoding his cortical neural activity as he attempted to speak
in both prompted and unstructured conversational contexts. Decoded words
were displayed on a screen and then vocalized with the use of
text-to-speech software designed to sound like his pre-ALS voice. On the
first day of use (25 days after surgery), the neuroprosthesis achieved
99.6% accuracy with a 50-word vocabulary. Calibration of the
neuroprosthesis required 30 minutes of cortical recordings while the
participant attempted to speak, followed by subsequent processing. On the
second day, after 1.4 additional hours of system training, the
neuroprosthesis achieved 90.2% accuracy using a 125,000-word vocabulary.
With further training data, the neuroprosthesis sustained 97.5% accuracy
over a period of 8.4 months after surgical implantation, and the
participant used it to communicate in self-paced conversations at a rate
of approximately 32 words per minute for more than 248 cumulative
hours. In a person with ALS and severe dysarthria, an
intracortical speech neuroprosthesis reached a level of performance
suitable to restore conversational communication after brief
training.