Binary classifier for a small range of the audio spectrum I am trying to detect a pitch in a narrow range of the audio spectrum with minimal samples. This corresponds to the rattling of certain mechanical systems. For example, the hum of an engine.

To do this, I am hoping to identify if there is a frequency at at a certain range such as 550hz-555hz.


I spoke with a learned fellow about this problem and he mentioned that there is a variation of the FFT that only targets the desired frequency range. What is this called?
I was hoping to avoid an amplitude (volume) training period by distinguishing peaks from white-noise in the frequency domain. Can anybody point me to a tunable parameter that will enable me to identify if a certain range has a peak? I was thinking of comparing the max height to the average.
I was wondering if anybody knew of a good method to do this.
It could have been Goertzel's algorithm, though it looks at a single frequency rather than a specific band.

Another approach is to apply modulation techniques to shift the central frequency of your range of interest into the baseband, aka "zoom FFT".

Your intuition about the max to average ratio is good. Another "peakedness" metric is the ratio of geometric mean to arithmetic mean.