Training AI To Transform Brain Activity Into Text

AI could one day help people with speech disabilities communicate Back in 2008, theoretical physicist Stephen Hawking used a speech synthesizer program on an Apple II computer to "talk." He had to use hand controls to work the system, which became problematic as his case of Lou Gehrig's disease progressed. When he upgraded to a new device, called a "cheek switch," it detected when Hawking tensed the muscle in his cheek, helping him speak, write emails, or surf the Web. Now, neuroscientists at the University of California, San Francisco have come up with a far more advanced technology—an artificial intelligence program that can turn thoughts into text. In time, it has the potential to help millions of people with speech disabilities communicate with ease AI approach that is akin to translating text in different languages. The underlying theory is the same in both cases—the goal is to convert one sequence of some arbitrary length into another—but the inputs are different, neural signals in the brain versus text.To test out their hypothesis, the researchers used human trials. The scientists implanted electrodes into the brains of four participants with epilepsy to monitor their speech. Each person then read sentences aloud from one of two datasets: a set of picture descriptions, composed of 30 sentences and 125 unique words, which contained 460 sentences and about 1,800 unique words.Each participant read 50 sentences aloud multiple timesthe researchers monitored their brain activity. Then, they input the data into a machine learning algorithm that could switch the brain waves into a string of numbers that encoded the sentences. In another portion of the system, the numbers were converted back into a sequence of words.the system improved as the researchers fed the system the initial sentences that the participants read aloud, to compare against. In one case, the system got 97 percent of the sentences correct, representing less errors than the average human transcriber. Still, the algorithm is only processing a small number of sentences and words compared to what a user would ultimately desire.