Speech brain–computer interfaces for communication rehabilitation: State‐of‐the‐art decoding models, clinical applications, and ethical challenges

Speech brain–computer interfaces (BCIs) represent an interdisciplinary neural engineering innovation enabling communication rehabilitation for individuals with anarthria or severe dysarthria. By decoding cortical activity into text or synthetic speech via nonmuscular pathways, this technology provides critical communication alternatives for patients with amyotrophic lateral sclerosis, poststroke aphasia, or locked‐in syndrome. Since early demonstrations of computer cursor control, significant advancements have been achieved in real‐time decoding of limited lexical sets, though challenges persist in system compatibility, decoding accuracy, transmission speed, and ethical governance. This review systematically evaluates state‐of‐the‐art speech decoding models, describes recent technological breakthroughs, and identifies unresolved challenges in clinical translation, while assessing cross‐disciplinary applications of speech BCIs in healthcare and assistive technologies.