Machine Learning Contest Aims to Improve Speech BCIs

For the next five months, machine learning gurus can try to best predict the speech of a brain-computer interface (BCI) user who lost the ability to speak due to a neurodegenerative disease. Competitors will design algorithms that predict words from the patient’s brain data. The individual or team whose algorithm makes the fewest errors between predicted sentences and actual attempted sentences will win a US $5,000 prize. The competition, called Brain-to-text ‘25, is the second-annual public, open-source brain-to-text competition hosted by a research lab part of the BrainGate consortium, which has been pioneering BCI clinical trials since the early 2000s. This year, the competition is being run by the University of California Davis’s Neuroprosthetics Lab. (A group from Stanford University hosted the first competition using brain data from a different BCI user.) For two years, the UC Davis research team has collected brain data from a 46-year-old man, Casey Harrell, whose speech is unin