[chuck-users] Analyse voice and choose animal
fiebrink at princeton.edu
Sun May 25 11:18:44 EDT 2008
This would be a great application for our new SMIRK toolkit (small
music information retrieval toolkit for MIR in ChucK), soon to be up
This is a great example of a problem that could be easily solved with
a machine learning algorithm, wherein you
1) Extract features from a training set of animal sounds
2) Use them to train a classifier (now available in chuck: kNN,
3) extract features from the mic input
4) use the trained classifier to classify the new inputs
You could start with playing with FFT, centroid, RMS, rolloff, and
other standard features, then use whatever features end up capturing
your idea of similarity the best.
I'll send a notice to this list once everything is totally up.
On 24-May-08, at 12:00 PM, chuck-users-request at lists.cs.Princeton.EDU
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> Here's what I'd like to achieve:
> There's a pool of samples of animals. There's a microphone. Someone
> talks to
> the microphone, the voice is analyzed and, based on a given similarity
> criteria, an animal is chosen.
> To be honest I don't know how this can be done and if it is easy or
> Should I try using FFT to determine, say, the main frequency and
> decide from
> there? Which other criteria should I be able to compare? Any links or
> samples to get me started?
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