Synchronizing Two Audio Tracks I would like to implement an algorithm that synchronizes two audio tracks.

The two tracks are very similar; you can imagine they are two recordings of sound (not necessarily music) from two microphones in the same room. This means they appear as one signal that passed through two different (linear) channels, with different additive noise.

I understand the first idea might be to look for the peak of their cross-correlation, but I am particularly interesting in finding literature on the topic, but all the papers I could find are either synchronizing two musical tracks (using chroma-based audio features), or synchronizing audio with a score. They also assume there might be time-warping, which is an unnecessary assumption in my case.
Chroma-based approaches are used when the tracks to align are two performances of the same material with widely different instrumentations - in which case you need to find the "lowest common denominator" which is harmony, melody, chord progression etc. Chroma are good for that - they totally abstract timbre, recording techniques. But you don't need those in your case.

As you have guessed, cross-correlation of the raw audio would be 1/ not very robust to noise, 2/ not very robust to differences in transducers (the two microphones might have very different responses) 3/ very costly if you have minutes of audio.

I suggest you to:


Extract a sequence of MFCC vectors from both signals. This way you'll have something of lower dimensionality and a bit more robust to noise and differences in transducers.
Optionally normalize the MFCC ("by design" coefficient 0 has more variance than coefficient 1 and so on...)... Ideally you'd want each row of the MFCC matrix to have variance 1.
Compute the cross-correlation of two matrices you get, along the time axis (that is to say, compute the 2D cross-correlation and just keep the data for the time axis).