Researchers Decode Internal Speech With Deep Learning

Researchers at Stanford University report experimental progress decoding internal speech by combining intracranial electrode recordings with deep-learning models, translating imagined words into near-real-time written text for a 52-year-old stroke survivor (participant T16) and volunteers with ALS. The approach reveals that the brain builds meaning gradually and, while still preliminary, represents a notable brain–computer interface breakthrough toward restoring communication.