Brain-computer interfaces are a groundbreaking technology that can help paralyzed people regain functions they’ve lost, like moving a hand. These devices record signals from the brain and decipher the user’s intended action, bypassing damaged or degraded nerves that would normally transmit those brain signals to control muscles.
Since 2006, demonstrations of brain-computer interfaces in humans have primarily focused on restoring arm and hand movements by enabling people to control computer cursors or robotic arms. Recently, researchers have begun developing speech brain-computer interfaces to restore communication for people who cannot speak.
As the user attempts to talk, these brain-computer interfaces record the person’s unique brain signals associated with attempted muscle movements for speaking and then translate them into words. These words can then be displayed as text on a screen or spoken aloud using text-to-speech software.
I’m a researcher in the Neuroprosthetics Lab at the University of California, Davis, which is part of the BrainGate2 clinical trial. My colleagues and I recently demonstrated a speech brain-computer interface that deciphers the attempted speech of a man with ALS, or amyotrophic lateral sclerosis, also known as Lou Gehrig’s disease. The interface converts neural signals into text with over 97% accuracy. Key to our system is a set of artificial intelligence language models – artificial neural networks that help interpret natural ones.
