The key was to think of this as a translation problem.
Ars Technica said:For people with limited use of their limbs, speech recognition can be critical for their ability to operate a computer. But for many, the same problems that limit limb motion affect the muscles that allow speech. That had made any form of communication a challenge, as physicist Stephen Hawking famously demonstrated. Ideally, we'd like to find a way to get upstream of any physical activity and identify ways of translating nerve impulses to speech.
Brain-computer interfaces were making impressive advances even before Elon Musk decided to get involved, but the problem of brain-to-text wasn't one of its successes. We've been able to recognize speech in the brain for a decade, but the accuracy and speed of this process are quite low. Now, some researchers at the University of California, San Francisco, are suggesting that the problem might be that we weren't thinking about the challenge in terms of the big-picture process of speaking. And they have a brain-to-speech system to back them up.
Speech is a complicated process, and it's not necessarily obvious where in the process it's best to start. At some point, your brain decides on the meaning it wants conveyed, although that often gets revised as the process continues. Then, word choices have to be made, although once mastered, speech doesn't require conscious thought—even some word choices, like when to use articles and which to use, can be automatic at times. Once chosen, the brain has to organize collections of muscles to actually make the appropriate sounds.
Beyond that, there's the issue of what exactly to recognize. Individual units of sound are built into words, and words are built into sentences. Both are subject to issues like accents, mispronunciations, and other audible issues. How do you decide on what to have your system focus on understanding?
The researchers behind the new work were inspired by the ever-improving abilities of automated translation systems. These tend to work on the sentence level, which probably helps them figure out the identity of ambiguous words using the context and inferred meaning of the sentence.
Typically, these systems process written text into an intermediate form and then extract meaning from that to identify what the words are. The researchers recognized that the intermediate form doesn't necessarily have to be the result of processing text. Instead, they decided to derive it by processing neural activity.
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