Hi Kassen, I read about it in this previous message from this mailing list, see item 2. Maybe I'm confused. I'm easily amused and easily confused! Haha! Les 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