Scientists have harnessed artificial intelligence to translate brain signals into speech, in a step toward brain implants that one day could let people with impaired abilities speak their minds, according to a new study. In findings published Wednesday in the journal Nature, a research team at the University of California, San Francisco, introduced an experimental brain decoder that combined direct recording of signals from the brains of research subjects with artificial intelligence, machine learning and a speech synthesizer.

A recent research study could give a voice to those who no longer have one. Scientists used electrodes and artificial intelligence to create a device that can translate brain signals into speech. This technology could help restore the ability to speak in people with brain injuries or those with neurological disorders such as epilepsy, Alzheimer disease, multiple sclerosis, Parkinson's disease and more. The new system being developed in the laboratory of Edward Chang, MD shows that it is possible to create a synthesized version of a person's voice that can be controlled by the activity of their brain's speech centers. In the future, this approach could not only restore fluent communication to individuals with a severe speech disability, the authors say, but could also reproduce some of the musicality of the human voice that conveys the speaker's emotions and personality.

The researchers worked with epilepsy patients undergoing brain surgery. Neuroengineers have crafted a breakthrough device that uses machine-learning neural networks to read brain activity and translate it into speech. An article, published Tuesday in the journal Scientific Reports, details how the team at Columbia University's Zuckerman Mind Brain Behavior Institute used deep-learning algorithms and the same type of tech that powers devices like Apple's Siri and the Amazon Echo to turn thought into "accurate and intelligible reconstructed speech." The research was reported earlier this month but the journal article goes into far greater depth. The human-computer framework could eventually provide patients who have lost the ability to speak an opportunity to use their thoughts to verbally communicate via a synthesized robotic voice.