Hearing over the din of noise is something that humans do a lot better than computers. A new mathematical technique promises to provide highly accurate models of sound, even with broadband noise in the picture. Why does this matter, aside from mathematical curiosity? For one, better sonic analysis could mean more realistic models of instruments and more flexible sound editing tools, inspiring a new generation of music software.
From our friend kokorozashi:
‘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 â€Å“algorithmâ€Â? that’s far more nuanced at transforming sound into a visual representation than current methods. â€Å“This outperforms everything in the market as a general method of sound analysis,â€Â? Magnasco says. In fact, he notes, it may be the same type of method the brain actually uses.’
Full article:
New mathematical method provides better way to analyze noise [Physorg.com]
This certainly wouldn’t be the first time new algorithms yielded scientific advances and musical advances alike. Even the famed (or infamous) AutoTune plug-in benefits from data processing techniques used in oil exploration. (Lesson: it takes a lot of science to make Jessica Simpson sing in tune. Sorry, couldn’t resist.) Of course, the converse is true, too: better sound processing can be very useful to a broad range of sciences, because, well, sound is just about everywhere.
[Updated] Tom Duff has managed to hunt down the actual paper so you can get this straight from the source:
Sparse time-frequency representations,
Timothy J. Gardner and Marcelo O. Magnasco [Proceedings of the National Academy of Sciences]
While I wouldn’t normally say this of academic papers, it has really pretty pictures. (Seriously: visual renderings of the analyses not only illustrate the point, but also happen to look gorgeous.)