ALIGN: Adversarial Learning for Generalizable Speech Neuroprosthesis

ArXi:2603.18299v1 Announce Type: new Intracortical brain-computer interfaces (BCIs) can decode speech from neural activity with high accuracy when trained on data pooled across recording sessions. In realistic deployment, however, models must generalize to new sessions without labeled data, and performance often degrades due to cross-session nonstationarities (e.g., electrode shifts, neural turnover, and changes in user strategy