>
>> I should clarify, it's an Owl with a low hooting sound at night in 
>> remote forest areas, in order to replicate it in the field we use 
>> subwoofers. I'll get more details on the exact frequencies when I'm in 
>> the office tomorrow.
>
>Ah, that seems like an owl might be easier than most other bird calls.
>
>A recording of a hoot would be even more useful, that way a display of
>the frequencies used over time could be calculated.
>
>> Making a list of times isn't a bad way to go, and I'll look at that some 
>> more.
>
>Sure, it would also be relatively easy to have it figure out all the closest
>matches and then play them and allow an operator to say y/n.   If you match
>the "fingerprint" of the sound instead of just a single frequency peak I 
>suspect you could get pretty good accuracy even when the same frequencies
>are created by thunder, coyotes, trees groaning in the wind, etc.


I think I'm on the right track now. What I figured out is that I can use 
whatever application I want to find the start time's for the region of interest 
and easily write those as a label track for audacity (see the .aup file its 
xmlish)

So python is up on the top of the list now. I also poked around and took a look 
at the new VAMP Plugin system which is directed towards analysis and could be 
integrated into Audacity or Sonic Visualiser ( http://www.sonicvisualiser.org/ 
).
The other application I've tinkered with is Praat ( 
http://www.fon.hum.uva.nl/praat/ )which is for speech recognition but that 
might be more hassle than it's worth.

This linked file has:
A sound sample
An audacity project with label track
A spectrogram screenshot 
A spectrogram text dump (looks like 10-60Hz is the region of interest)
http://ftp.dfg.ca.gov/Public/RAP/Projects/GGOW/GGOWspectrum.zip

Thanks for the help, I guarantee at least one lugod talk later this year (after 
I finish my thesis) in exchange.

Alex
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