Hello,<br><br>There's an external for pd / max-msp called soundspotter designed for doing the kind of thing you want: <a href="http://www.soundspotter.org/">http://www.soundspotter.org/</a><br><br>I'm not intimately familiar with it's workings, but it is open-source and Michael Casey has written several papers on the subject which you'll find under 'Research' on that page. So, if you definitely want to use ChucK (I'd suggest pd with that external may be the easiest route in the short term), there'll be lots of useful information there.<br>
<br>If you did what you described with FFT, you would probably be vaguely on the right track, but I'm afraid it could turn out to be quite a long track...<br><br>Good luck, it sounds like a fun idea; and soundspotter should be a perfect fit.<br>
<br>Cheers,<br>Peter<br><br><div class="gmail_quote">On Fri, May 23, 2008 at 5:17 PM, Nuno Godinho <<a href="mailto:eu@nunogodinho.com">eu@nunogodinho.com</a>> wrote:<br><blockquote class="gmail_quote" style="border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">
Hi,<br>
<br>
Here's what I'd like to achieve:<br>
<br>
There's a pool of samples of animals. There's a microphone. Someone talks to<br>
the microphone, the voice is analyzed and, based on a given similarity<br>
criteria, an animal is chosen.<br>
<br>
To be honest I don't know how this can be done and if it is easy or hard.<br>
Should I try using FFT to determine, say, the main frequency and decide from<br>
there? Which other criteria should I be able to compare? Any links or<br>
samples to get me started?<br>
<br>
Thanks,<br>
Nuno<br>
<br>
<br>
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