Measuring the "frequency stability" of a signal I'm thinking about ways to automatically identify and analyze lots of musical instrument samples, and would like to find the part of the sample that's the most stable in frequency, without any accidental vibrato or anything.  My first thought was to do a sliding FFT and find the "width" of the peaks (maybe fitting a parabola to many of the neighboring points?), since a constant frequency chunk will produce a narrow peak (green) and one wavering in frequency should produce a wider peak (red):



On a spectrogram the red is a slightly wiggly line, and the green is a more straight line.

Time domain is ok, too.  Some kind of "slide the signal past itself and look for sections that interfere with each other in a constant way instead of phasing in and out"? 

But I'm not sure how easy or reliable this method would actually be.  Any other ideas?
Your technique might work, provided you window and so on correctly, but it does not really strike me as the right approach for pitch vibrato for a lot of reasons, mostly that the change in pitch is very small compared to other things which could change the "width" of your spectrum (eg, timbre).

I think you'd be better off actually tracking the fundamental pitch in the time domain using a technique like YIN and seeing how much it varies over time.