A Simpsons episode where Homer's half-brother invents a machine to translate Maggie's baby-talk has come closer to reality with clever new software.
A Simpsons episode where Homer's half-brother invents a machine to translate Maggie's baby-talk has come closer to reality with clever new software.
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CHICAGO - A computer programme that learns to decode sounds from different languages in the same way that a baby does helps to shed new light on how people learn to talk, researchers said.
They said the finding casts doubt on theories that babies are born knowing allthe possible sounds in all of the world's languages.
"The debate in language acquisition is around the question of how much specific information about language is hard-wired into the brain of the infant and how much of the knowledge that infants acquire about language is something that can be explained by relatively general purpose learning systems," said James McClelland, a psychology professor at Stanford University in Palo Alto, California.
McClelland says his computer programme supports the theory that babies systematically sort through sounds until they understand the structure of a language.
"The problem the child confronts is how many categories are there and how should I think about it. We're trying to propose a method that solves that problem," said McClelland, whose work appears in the Proceedings of the National Academy of Sciences.
Expanding on some existing ideas, he and a team of international researchers developed a computer model that resembles the brain processes a baby uses when learning about speech.
He and colleagues tested their model by exposing it to "training sessions" that consisted of analysing recorded speech in both English and Japanese between mothers and babies in a lab.
What they found is the computer was able to learn basic vowel sounds right along with baby.
"It learns how many sounds there are. It figures that out," he said in a telephone interview.
And if the computer can do it, he said, a baby can, too.
"In the past, people have tried to argue it wasn't possible for any machine to learn these things, and so it had to be hard-wired (in humans)," he said. "Those arguments, in my view, were not particularly well grounded."
