Feature extraction in audio spectrogram I have audio and its spectrogram of the words in English language. (A spectrogram is a frequency domain representation of a signal) Consider the words: chain, change, chair, chapter. As you can notice, the 'ch' sound is common among the words considered. 

Is there an algorithm that will allow me to identify which part of the spectrogram (data) is common between the spectrograms of the words? In other words, is there an algorithm that can identify the part of the spectrogram that represents 'ch' sound in each of the words?
The "ch" sound is called a phoneme. Automatic speech segmentation on the phoneme level (as opposed to word or sentence) will allow you to extract each phoneme from the speech samples. This is sometimes referred to as phoneme segmentation. Several papers for this are available in the literature.

Once you have the phonemes extracted, you can compute distances/similarities between them (in some feature space). An example feature representation could be MFCC.