(wow) Words Of Wonders Level 1272 Answers – This stamp-sized array of electrodes is placed directly on patients’ brains and can detect slight fluctuations in voltage when they speak. A pair of neural networks then translate this activity into synthesized speech.
One day, people who have lost the ability to speak may get their voices back. New research shows that electrical activity in the brain can be decoded and used to synthesize speech.
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Published Wednesday in the journal Nature, the study published data from five patients whose brains had already been monitored for seizures with stamp-sized electrode arrays placed directly on the surfaces of their brains.
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When participants read hundreds of sentences — some from classic children’s tales like Sleeping Beauty and Alice in Wonderland — the electrodes tracked subtle fluctuations in brain voltage, which the computer model learned to associate with their speech. This translation was achieved through an intermediate step, which linked brain activity to complex imaging of the vocal tract – a metric based on recent research that found that the brain’s speech centers can process lip, tongue, and jaw movements. Let’s encode.
“It’s a very beautiful technique,” says Christian Harf, a postdoctoral researcher at Maastricht University who studies similar patterns of brain activity in speech.
The device represents the latest in a rapidly evolving effort to map the brain and engineer ways to understand its activity. A few weeks ago, a different team, including Herv, published a model in the Journal of Neuroengineering that synthesized speech from brain activity using a slightly different approach, without simulating the vocal system.
“Decoding speech is an exciting new frontier for brain-machine interfaces,” says Cynthia Chastak of the University of Michigan, who was not involved in either study. “And there is a subgroup of the population that actually makes great use of it.”
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Both teams, as well as other researchers around the world, hope to help people whose ability to speak suffer from conditions such as amyotrophic lateral sclerosis (ALS) – the neurodegenerative disorder better known as Lou Gehrig’s disease – and stroke. robbed from Although the speech centers in their brains are still intact, patients remain unable to communicate, being closed off from the world around them.
Previous efforts have focused on using brain activity to allow patients to write words one letter at a time. But the typing speeds of these devices top out at around eight words per minute – nowhere close to natural speech, which runs at around 150 words per minute.
“The brain is the most efficient machine that has evolved over thousands of years, and speech is one of the defining characteristics of human behavior that sets us apart from all non-human primates,” says nature researcher Gopala Anumanshipali of the University of California, Berkeley. Berkeley. , San Francisco. “And we take it for granted — we don’t even realize how complex this locomotor behavior is.”
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While the study results are encouraging, it will take years of additional work before the technology is available for use by patients and adapted for languages other than English. And these efforts are unlikely to help people who have suffered damage to the speech centers of the brain, such as traumatic brain injuries or wounds. The researchers also stress that these systems are not equivalent to brains reading: Studies have only monitored the brain regions that control vocal system movements during conscious speech.
“If I’m just thinking, ‘Oh my God, this is a really tough day,’ I don’t control my facial muscles,” Harf says. “The meaning is not what we are decoding here.”
To translate thoughts into sentences, Anumanshipali and her colleagues used electrodes placed directly on the surface of the brain. Although invasive, this direct observation is the key to success. “Because the skull is really hard and really acts like a filter, it doesn’t allow all the rich activity that’s going on down below to escape,” says Anomanspally.
After collecting the high-resolution data, the researchers ran the recorded signals through two artificial neural networks, which are computer models that mimic brain processes, to find patterns in complex data. The first network approximated how the brain signals the lips, tongue and jaws to move. The second converted these movements into synthetic speech, and trained the model using recordings of the participants’ speech.
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Then came the real test: Can other humans understand synthetic speech? To get the answers, the researchers recruited a group of 1,755 native English speakers using Amazon’s mechanical platform Turks. Subgroups of these listeners were assigned 16 different tasks to judge the intelligibility of both words and sentences.
The brain is the most efficient organ that has evolved over thousands of years, and speech is one of the defining characteristics of human behavior that sets us apart from all non-human primates. Written by Gopala Anomanchipalli, University of California, San Francisco.
Participants listened to 101 sentences of synthesized speech and then tried to copy what they heard by choosing from a set of 25 or 50 words. They were correct 43 and 21 percent, respectively, depending on the number of words to choose from.
Not every route was equally conceivable. A few simple sentences, such as “Is this option safe?” – I got the correct messages every time. But more complex sentences, such as “We’ll have a Chablis on the evening of the 12th,” came out less than 30 percent of the time.
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Some sounds are also more easily decoded than others. Sustained signals, like the sh in “Ship,” came through the analysis cleanly, while quick bursts of noise—like the B in “Bat”—were smooth and blended.
Although the output is not perfect, Chester points out that the data used to train the system is still too small. “Obviously they’re still working with one hand behind their back because they’re limited to epilepsy surgery and epilepsy patients,” she says, alluding to the potential future posed only by brain-to-speech translation. Adding System might be a bit better. “I’m cautiously excited.”
The authors of the Nature study used a two-step process to make their synthesized speech more legible. But in principle, it should be possible to go directly from brain activity to speech without using a simulated audio system as an intermediary, as shown in a Journal of Neuroengineering study.
The audio clip—produced using a new method—disclosed in the Journal of Neuroengineering—features nine examples of a research participant reading a word, followed by a synthesized version of the word generated by his or her brain activity.
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In this work, the researchers recorded the brain activity and speech of six people who had surgery to remove a brain tumor using a network of electrodes in the brain, as in the Nature study. The team then trained a neural network to find connections between each participant’s spoken words and brain activity, and designed the system to run on just eight to 13 minutes of voice input—all the data they analyzed. Could collect in between.
“You just have to imagine how stressful the situation is: A surgeon opens up the skull and then places this grid of electrodes directly on it, and they do this by finding where the cancer stops and where the vital cerebral cortex [brain material] begins.” Happens,” Harf says. , “Once that’s done, they have to figure out what to cut – and during that time, our data is recorded.”
The researchers then fed the neural network’s output into a program that converted it into speech. Unlike the Nature study, which attempted to put together entire sentences, Harf and his colleagues focused on building single words.
It’s difficult to directly compare the performance of the two methods, stresses Mark Slutsky of Northwestern University, co-author of the Journal of Neural Engineering study. But they do show some similarities. “Some of the scales we’ve used together seem to be quite similar in performance – at least for some subjects,” he says.
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There are still significant hurdles to overcome before this technology can get into the hands — or minds — of patients. First, the models in both studies are based on people who can still talk, and have not yet been tested on people who used to talk but can no longer.
“There’s a very basic question … whether or not these algorithms will work,” says study author Edward Chang, MD, professor of neurosurgery at the University of California, San Francisco. “But we’re getting there; we’re getting closer to it.”
Anumanchipali and his team have attempted to address this in a number of experiments by training participants who do not make sounds, but only speak sentences silently. While it successfully produced artificial speech, syllables were less accurate based on spoken input. Furthermore, pantomime still requires patients to be able to move the face and tongue—something not obvious to people with neurological problems that limit their speech.
“The patients you care so much about [using] it’s really not going to help,” Slutsky says of the mock tests. While he sees the work as powerful evidence of what is now possible, the field still struggles to make the leap for those who can no longer speak.
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