Stanford: Researchers at Stanford University have unveiled a groundbreaking brain-computer interface (BCI) capable of decoding imagined speech, the silent words people think, and converting them into spoken language. This innovation offers new hope for individuals with severe paralysis who have lost the ability to speak. According to Qatar News Agency, unlike previous BCIs that relied on brain signals generated during attempts to move the mouth or vocal cords, the Stanford team focused on decoding inner speech, or silent self-talk. Lead author Erin Kunz explained that this is the first time they've managed to understand what brain activity looks like when you just think about speaking, emphasizing the potential for more natural communication for those with motor impairments. The study involved four participants with paralysis due to ALS or brainstem stroke. Microelectrode arrays were implanted in their motor cortex, the brain region responsible for speech. Participants were asked to either attempt to speak or silently imagine words. Using AI models, researchers decoded neural patterns associated with phonemes and reconstructed them into full sentences. Results showed that imagined speech produced neural signals similar to actual speech attempts, achieving up to 74% accuracy in real-time word recognition despite weaker signals. To address privacy concerns, the team developed a thought password system that activates decoding only when a specific phrase is imagined. This safeguard was successful 98% of the time, ensuring users maintain control over when their thoughts are translated.