[chuck-users] Analyse voice and choose animal

[Rebecca Fiebrink]

Hi Nuno,

This would be a great application for our new SMIRK toolkit (small  
music information retrieval toolkit for MIR in ChucK), soon to be up  
at http://smirk.cs.princeton.edu.

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,  
adaboost)
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.

Cheers,
Rebecca


On 24-May-08, at 12:00 PM, chuck-users-request at lists.cs.Princeton.EDU  
wrote:

> Send chuck-users mailing list submissions to
> 	chuck-users at lis
> Hi,
>
> 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  
> hard.
> 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?
>
> Thanks,
> Nuno
>
>