Revolutionary Brain Chip Translates Silent Thoughts into Actual Speech

A team at Stanford University has developed a brain-computer interface that converts silently thought words into speech. The team envisions a future where communication may one day be possible through thought alone.

Scientists from Stanford University have developed a new brain-computer interface (BCI) that can translate silent thoughts in the brain into actual speech. While previous technologies could only detect signals that occurred when a person was actively trying to speak, this new system can also decode words that a person is silently thinking in their head.

The study involved four participants with severe paralysis due to ALS and brainstem stroke. One of the participants could only communicate by looking up for “yes” and sideways for “no.” Microscopic electrode arrays were implanted into the subjects’ motor cortex, the region of the brain that controls speech-related movements. This technology was developed by the BrainGate BCI consortium, which has been working on brain-computer interfaces for many years.

A Major Breakthrough Was Achieved

The electrodes recorded brain activity related to speech and movement. Participants were given words that they were asked to both say aloud and merely imagine. Afterwards, artificial neural networks analyzed the patterns in this brain activity to distinguish phonemes (the smallest units of sound in speech). The system then converted these phonemes into words and sentences in real-time.

According to the results, the words participants merely thought about produced weaker signals compared to actual speech. Despite this, the system successfully managed to decode silent speech with an accuracy rate of up to 74%.

The study’s lead author, Erin Kunz, a neuroscientist at Stanford University, stated, “For the first time, we’ve been able to understand what brain activity looks like when someone is just thinking about a conversation. For people with severe speech and motor impairments, neuroprosthetics that recognize inner speech could make communication easier and more natural.”

Frank Willett, a professor of neurosurgery and a member of the research team, emphasized that trying to speak can be exhausting for people with partial paralysis, and can even lead to issues like shortness of breath. Decoding silent speech directly from the brain is seen as a major step that could eliminate these barriers.

Privacy Concerns and Future Vision

Another significant finding in the study was the issue of privacy. The system sometimes detected participants’ unsolicited thoughts; for example, their counting of numbers during a visual task was recorded. To prevent this, the team developed a security lock that activates only with a specific “imaginary password.” In tests, the phrase “chitty chitty bang bang” blocked unwanted decodings 98% of the time.

Although still in the experimental stage, the Stanford team believes this work shows that it may be possible to communicate solely with thoughts in the future. According to the researchers, language-based brain-computer interfaces could one day allow people to communicate as naturally, quickly, and freely as if they were speaking.

Meanwhile, interest in brain-computer interfaces is growing not just in the scientific community, but also in the tech world. A new startup called Merge, backed by OpenAI CEO Sam Altman, aims to compete with Elon Musk’s Neuralink project.

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