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Author: admin | 03.05.2015 | Category: One Ear Ringing

Hi, here we provide you APK file of "Tinnitus Stereo" to download and install for your mobile. I’m working (collaboratively, with Jenny Lentz) on a research project aimed at developing tools to accurately characterize tinnitus. The final, full version of the algorithm is a bit more complicated, and what you do with the samples isn’t necessarily simple, but this is the essence of the method. No, today I’m writing about how, in coding up this algorithm, I accidentally bestowed upon myself the ability to synthesize cool organ sounds. One dimension we’re probing consists of a parameter that governs the spacing of the individual components. The components are spaced logarithmically such that each is some number┬ák times the value of the next lower component. This one is the same as the first, except for the filter (also Gaussian, in case you’re wondering), which, in this sound, is shifted to lower frequencies and has a smaller bandwidth. Not terribly pleasant to listen to, but interesting, I think, since the only difference between this and the previous one is the bandwidth of the components.

High-pitched, noisy, a bit warbly… sounds like (a reasonably close approximation to) crickets to me. When I get the algorithm finished, I’ll post the code and write some more about MCMCP in general.
Is the objective to define the exact frequency of a patient’s subjective tinnitus tone and use that data to generate a phase inverted signal that would cancel out their tinnitus?
Unfortunately, I don’t think you can cancel tinnitus with a perfectly out-of-phase signal, though that would be extremely cool if you could.
We’re also planning on testing the algorithm with predetermined categories in people without tinnitus. First, you pick a point in your stimulus space and generate a sound that corresponds to that point.
Or, more accurately, the component’s mid-points (or center frequencies) are spaced logarithmically. Then you probabilistically pick a second point and generate a sound that corresponds to┬áthat point.

The sounds we’re generating are, in general, complex, by which I mean that they have non-simple spectral properties. The third and fourth govern the location and bandwidth of the filter that scales the components. Each component is a Gaussian curve with a standard deviation that scales up (also logarithmically) with the center frequency. It doesn’t sound that much like chorus…although my experience with effects pedals is limited to guitars, not crickets or organ-like sounds, so what do I know? Tinnitus cancelling headphones might just win you a Nobel prize – at least in the hearts of the thousands of people that suffer from it.
Whichever sound they choose as better defines your new first point in stimulus space, and you go back to the beginning of the algorithm.

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