Detection of wobbling sound with rising notes In an audio file I would like to find calls of a specific bird specie, one that makes wobbling sound with rising notes. Can you recommend what would be the best audio feature to calculate in time or frequency domain to capture its essence? 

Among others I tried MFCC, but the results were not promising (or perhaps my implementation poor) .

[Edit] 

In this post I explained briefly the problem and included exemplary audio file with spectrogram: Example. 

Here is another example. All marked areas contain kiwi (famous flightless bird from New Zealand) calls I am trying to identify. Mark that the original audio is very noisy; presented spectrogram is a result of applying high-pass filter and spectral subtraction on areas identified as noise-only.
I would start with following set of parameters:


MFCC's (I that know you tried it, but stay with me) without static energy (1'st coefficient)
Some descriptors from MPEG-7, like: Spectral Flatness, Harmonicity, Fundamental frequency, Spectral Spread, etc. You can find out more about them here: click or in this great book: MPEG-7 Audio and Beyond


You should also include $\Delta$'s and $\Delta\Delta$'s of MFCC's and Spectral Flatness. They should really improve accuracy. You can also try to calculate these for other parameters. Having that, you can start with Gaussian Mixture Model or Support Vector Machine (I think that GMM will be suitable for that task). After training your model simply validate it on testing set (seems obvious but I've seen many projects where people tested their Machine Learning algorithms on training set with added noise or, what's even worse, same training data).

After this, you should perform Feature Optimisation. This is important part, as some of the features are irrelevant (i.e. Spectral Flatness for few first filter banks, while bird's chirp has higher frequencies). Nice publications with many algorithms for that purpose can be found here: click,   click.
Good luck!