[Sursound] Spherical microphone array

2013-10-18 Thread Alexis Shaw
Hello all.

I was wondering what people thought of the usefulness of a 10cm
diameter spherical microphone array with 1000 mems detectors. (I'm Thinking
of using ADMP621s)

I know that this has a kr of about 3.2 but with the large number of
microphones I was thinking it might be possible to get a 4th order result
without significant spatial aliasing. Especially if The pattern was chosen
to minimise spatial aliasing.

In order to complement this I was thinking of increasing the frequency
response al lower frequencies with a second, open spherical array ala the
work of the university of sydney.

Do you think that this would be a worthwhile exercise.
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[Sursound] curiosities

2013-10-18 Thread Matthew Palmer
Hi, I've never really heard anything in ambisonics or wfs. I'm saving up
money for speakers currently. I'm ultimately interested in helping to build
audio tools/environments for virtual reality (http://www.oculusvr.com/ +
http://sixense.com/hardware/wireless = tools to help build localization
programs +3d visualizers, etc). If anyone liked to help, let me know. I'm
stuck on Phase 1 for a bit because of funds.

Anyways, is the movement of the microphone interesting to hear? Like
walking forward or if you're holding doing baton movements with it or
something. Because you're not moving when you're listening to it (it
creates an interesting effect in VR visually  can even cause nausea if
you're moving around too much or at least it did for me).

I think ultimately I'm wanting to know how movement (of sound  the
microphone too)  space could be used to create new kinds of music. Can you
make a synth that snakes around in the air (can the sound be localized that
precisely?) Could percussive elements sound like they were orbiting each
other, etc?

What kinds of hardware does it to take to be able to hear that?
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Re: [Sursound] Acoustic echoes reveal room shape

2013-10-18 Thread Matthew Palmer
Lol, didn't read this one, jinxing with these people. - matt


On Thu, Oct 17, 2013 at 1:43 PM, Aaron Heller hel...@ai.sri.com wrote:

 Interesting paper in PNAS, from July. I believe it is open access, so
 anyone can read/download.   Aaron

 http://www.pnas.org/content/110/30/12186.short

 The supplemental information (SI) shows some of the equipment and more
 math.

 I. Dokmanić, R. Parhizkar, A. Walther, Y. M. Lu, and M. Vetterli, “Acoustic
 echoes reveal room shape,” Proceedings of the National Academy of Sciences,
 vol. 101, no. 30, pp. 12186–12191, Jul. 2013.


 Abstract

 Imagine that you are blindfolded inside an unknown room. You snap your
 fingers and listen to the room’s response. Can you hear the shape of the
 room? Some people can do it naturally, but can we design computer
 algorithms that hear rooms? We show how to compute the shape of a convex
 polyhedral room from its response to a known sound, recorded by a few
 microphones. Geometric relationships between the arrival times of echoes
 enable us to “blindfoldedly” estimate the room geometry. This is achieved
 by exploiting the properties of Euclidean distance matrices. Furthermore,
 we show that under mild conditions, first-order echoes provide a unique
 description of convex polyhedral rooms. Our algorithm starts from the
 recorded impulse responses and proceeds by learning the correct assignment
 of echoes to walls. In contrast to earlier methods, the proposed algorithm
 reconstructs the full 3D geometry of the room from a single sound emission,
 and with an arbitrary geometry of the microphone array. As long as the
 microphones can hear the echoes, we can position them as we want. Besides
 answering a basic question about the inverse problem of room acoustics, our
 results find applications in areas such as architectural acoustics, indoor
 localization, virtual reality, and audio forensics.
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