Speech discrimination from animal sound i am looking for discrimination of speech from animal sound if you take a 150ms frame of speech and bird as shown below, what feature can i extract from them so that i can effectively state the difference 



zero crossings ?
cross correlation of successive frames seems high in bird sound ? isn't it 
any other feature from your side ?



one more example in above fig black-speeches,yellow siren,red bird,safron heavy wind the spikes are foot steps 

above figure shows the difference in formant positions on spectrogram
in bird sounds the formants are differently spaced and less formants 

will anything could be extracted from this analysis

the reason is i am looking for unsupervised(with out any training or SVM) speech discrimination form animal sounds because both are voice but computers cant classify the difference unless they are trained by any nueral network which need huge memroy and training database
The essence of your problem is one of Voice Activity Detection (VAD). This is a well researched topic and you should investigate the available algorithms - there are many papers available online, here for example

You should apply a VAD algorithm to the signal and replace non-speech areas with silence, you can then look at the specific edge cases which are concerning you, such as animal sounds have being incorrectly considered speech.

For the case of animal sounds you may want to investigate Formant Detection (for example this paper) since as you pointed out there is a distinction between them. You may also want to consider developing a heuristic based on your own empirical data about the differences. You can take many signal features such as the fundamental frequency, the signal power/amplitude, peakedness etc... and weight these appropriately to give you a confidence rating about the likelyhood of it being animal rather than human speech. This is a fuzzy approach, you would need to iterate a lot on the weightings and metrics.