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Sound investment: A new mathematical method provides a better way to analyze noise

Humans have 200 million light receptors in their eyes, 10 to 20 million receptors devoted to smell, but only 8,000 dedicated to sound. Yet despite this miniscule number, the auditory system is the fastest of the five senses. Researchers credit this discrepancy to a series of lightning-fast calculations in the brain that translate minimal input into maximal understanding. And whatever those calculations are, they're far more precise than any sound-analysis program that exists today.

In a recent issue of the Proceedings of the National Academy of Sciences, Marcelo Magnasco, professor and head of the Mathematical Physics Laboratory at Rockefeller University, has published a paper that may prove to be a sound-analysis breakthrough, featuring a mathematical method or "algorithm" that's far more nuanced at transforming sound into a visual representation than current methods. "This outperforms everything in the market as a general method of sound analysis," Magnasco says. In fact, he notes, it may be the same type of method the brain actually uses.

Magnasco collaborated with Timothy Gardner, a former Rockefeller graduate student who is now a Burroughs Wellcome Fund fellow at MIT, to figure out how to get computers to process complex, rapidly changing sounds the same way the brain does. They struck upon a mathematical method that reassigned a sound's rate and frequency data into a set of points that they could make into a histogram -- a visual, two-dimensional map of how a sound's individual frequencies move in time. When they tested their technique against other sound-analysis programs, they found that it gave them a much greater ability to tease out the sound they were interested in from the noise that surrounded it.

One fundamental observation enabled this vast improvement: They were able to visualize the areas in which there was no sound at all. The two researchers used white noise -- hissing similar to what you might hear on an un
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Contact: Kristine Kelly
kkelly@rockefeller.edu
212-327-7146
Rockefeller University
26-Jul-2006


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