Compare two spectogram to find the offset where they match algorithm

Question

I record a daily 2 minutes radio broadcast from Internet. There\'s always the same starting and ending jingle. Since the radio broadcast exact time may vary from more or les

Answer 1

If you already know the jingle sequence, you could analyse the correlation with the sequence instead of the cross correlation between the full 15 minutes tracks.

To quickly calculate the correlation against the (short) sequence, I would suggest using a Wiener filter.

Edit: a Wiener filter is a way to locate a signal in a sequence with noise. In this application, we are considering anything that is "not jingle" as noise (question for the reader: can we still assume that the noise is white and not correlated?).

( I found the reference I was looking for! The formulas I remembered were a little off and I'll remove them now)

The relevant page is Wiener deconvolution. The idea is that we can define a system whose impulse response h(t) has the same waveform as the jingle, and we have to locate the point in a noisy sequence where the system has received an impulse (i.e.: emitted a jingje).

Since the jingle is known, we can calculate its power spectrum H(f), and since we can assume that a single jingle appears in a recorded sequence, we can say that the unknown input x(t) has the shape of a pulse, whose power density S(f) is constant at each frequency.

Given the knowledges above, you can use the formula to obtain a "jingle-pass" filter (as in, only signals shaped like the jingle can pass) whose output is highest when the jingle is played.